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Pivoting toward a STEM career with the NSF ExLENT program at Chicago State University

By Ken Ogata

The National Science Foundation (NSF) has announced the Experiential Learning for Emerging and Novel Technologies (ExLENT) program, which provides experiential learning opportunities in emerging-technology fields such as artificial intelligence (AI), biotechnology, and microelectronics.

The ExLENT program hopes to increase access to STEM careers for people in nontraditional education pathways or individuals already in STEM who wish to retool into a different field of technology. Issues such as climate change and obtaining clean energy require a diverse set of perspectives to solve. Through the ExLENT program, the NSF strives to increase opportunities within technology fields crucial to solving these issues and to make sure that people are not left behind in STEM.

Since the program aims to serve individuals of many different backgrounds, the ExLENT program is divided into three tracks: Pivots, Beginnings, and Explorations.

Programs in the Pivots track will provide opportunities for individuals not currently enrolled in post-secondary-education programs (i.e., 4-year universities and associate’s degree programs) but who wish to learn the skills required to excel in emerging-technology fields.

The Beginnings track is for people with career experience and or degrees in STEM who wish to deepen their knowledge and advance their careers with more hands-on learning.

The Explorations track focuses on creating career pathways for individuals with limited STEM education. Projects in this track will offer specialized learning opportunities to help people build a strong foundation for a career in technology.

The three tracks in the ExLENT program, according to NSF (Section II):

PivotsIndividuals in non-emerging technology careers who wish to upskill and pivot to work in emerging fields; not currently enrolled in post-secondary-education programs.
BeginningsIndividuals with degrees or certificates in STEM who hope to deepen their knowledge and skills in emerging-technology fields.
ExplorationsIndividuals with limited or no specialized STEM education or enrolled in nontraditional educational pathways, such as self-learners.

All programs focus on providing mentorship for participants and lowering the barriers to entry that exist in the realm of technology. NSF expects that these experiential learning opportunities will assist historically underrepresented groups and underserved individuals in succeeding in emerging-technology areas.

One of these programs is the Chicagoland Partnership for Semiconductor and Microelectronics Experiential Learning (Mic2ExL) project, organized by Chicago State University in partnership with community organizations, Argonne National Laboratory, and industry partners such as Quilt, a Chicago nonprofit organization. The program hopes to address the need for increased domestic production of electronic components by mentoring individuals in the local Illinois tech sector.

Dr. Moussa Ayyash, director of the Center for Information & Security Education and Research (CINSER) at Chicago State University and Principal Investigator for this program believes that the focus on microelectronics and semiconductors will help increase interest in the field in the Chicagoland area.

“We picked microelectronics and semiconductors because we believe it’s [a good fit] for an experiential learning program. It’s a well-established field and we have the resources to support this as a university,” Ayyash said.

The Mic2ExL project follows a 3-phased approach to help participants get their foot in the door of the microelectronics and semiconductors industry. The first phase will help participants gain foundational knowledge about the industry, followed by experiential learning projects at Argonne National Laboratory to see real-world applications.

“We’ll connect them with mentors from the lab, where they will work on real problems and see real-world applications,” Ayyash said. “After they finish the first and the second phases of Mic2ExL, we’ll connect each participant with an employer to spend 50 hours practicing what they have learned at a company. The last phase of Mic2ExL will be a job fair.”

The project belongs to the Pivots track of the ExLENT program and is appropriately geared towards individuals who hope to gain foundational knowledge in the field of microelectronics and semiconductors, regardless of their background.

“We’re taking people who maybe don’t have any background—you can be a history major, physics, can be computer science . . . as long as you have interest in exploring a new area,” Ayyash said. “I’m an electrical engineer. This is my degree, and I know this can be boring to somebody and exciting to somebody else. That’s why we have the exposure aspect. We are exciting them and we are hoping those who finish all three phases will be ready to work at the entry level.”

Another key goal of the program is to increase participation of individuals from underrepresented minority groups in the Chicagoland area, specifically in the semiconductor and microelectronics industry. Ayyash hopes that the Mic2ExL project’s experiential-learning approach will help bridge the gap for individuals who find it hard to break into the industry because of their background.

“This is a field that has a lot of opportunities and [we want to show them that] this is what it takes to get there. We’re trying to get you to get your hands dirty working with this a little bit. It’s one of the ways to remove the barriers for them,” Ayyash said.

Another project in the Midwest funded by the ExLENT program is the Sensor Technology as a Vehicle to Cultivate Experiential Learning for Emerging and Novel Technologies project, headed by the Illinois Institute of Technology. This project is in response to the U.S. CHIPS and Science Act of 2022, which called for the need to increase domestic production of semiconductors and microelectronics to combat the chip shortage caused by the COVID-19 pandemic.

This project aims to train a skilled workforce in the field of sensor technology and will be geared towards preparing veterans and underrepresented and underserved groups in STEM. With the rise of sensor technology in modern and industrial applications, this program hopes to assist individuals through mentored research and internship training.

Other awardees of the ExLENT program include Michigan Technological University, the University of California–Berkeley, Carnegie Mellon University, and the University of Cincinnati. These projects range from preparing autistic students for the AI workforce to experiential learning for emerging biotechnology careers. For more information on projects within the ExLENT program, see the table below.

The ExLENT program strives to address the lack of opportunities that many individuals face in their journey towards a career in STEM. A diverse set of perspectives is crucial to innovation in technology, and the ExLENT program is a large step towards a more-accessible STEM community.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities, including our Data Science Student Groups Community webinar series.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Summary of Awardees in the ExLENT Program*

TitleTrackDescription
Chicagoland Partnership for Semiconductor and Microelectronics Experiential Learning (Mic2ExL)
(Chicago State University)
PivotsProvide experiential learning opportunities to individuals who hope to gain foundational knowledge in the field of microelectronics and semiconductors,
Experiential Learning for Emerging Biotechnology Careers
(HudsonAlpha Institute For Biotechnology)
BeginningsImmerse nontraditional students from community colleges in the field of biotechnology to address the shortage of trained biotech workers.
Introducing Molecular Modeling Experiences to Underrepresented Students
(Research Foundation of the City University of New York)
BeginningsProvide technical skills needed by the biotechnology industry to undergraduate students from underrepresented backgrounds.
Preparing Autistic Students for the AI Workforce
(The Pennsylvania State University, Carnegie Mellon University)
BeginningsAddress the shortage of talent in the field of artificial technology and also the discrimination that autistic students face due to social stigma; aims to teach team collaboration and communication skills through AI-focused projects; help community college students with autism obtain summer internships and careers in AI.
VETS-HASTE: Veterans SkillBridge through Industry based Hardware Security Training and Education
(University of Florida)
PivotsFight security vulnerabilities in commercial and military cyberinfrastructure by providing training to diverse groups of veterans.
Reskilling Education Via Advanced Manufacturing Practicum
(University of Cincinnati)
PivotsSupport traditionally underrepresented populations in STEM by helping them pivot into careers in manufacturing. This includes individuals who have some background in stem, but, due to major life events, have either remained unemployed for some time or require upskilling to work in the manufacturing sector.
Workforce Innovation and Inclusion in Semiconductors and Emerging Research Areas
(University of California–Berkeley)
BeginningsAddress urgent demand for workers in the semiconductor industry; provide experiential learning and professional development programs with leading industry partners and at the University of California campuses for transfer students, women, first-generation students, and underrepresented minorities.
Experiential Learning for the Mechatronics Workforce in the Upper Peninsula and Northern Michigan
(Michigan Technological University)
BeginningsMechatronics is the development of automation for industrial applications. The project will prepare a cohort of diverse participants in Michigan for robotics, mechanics, cybersecurity, and AI in industrial settings.
*Among many others; for the full list, visit: Full NSF Awardee List for the ExLENT Program

Using Deep Learning to Accelerate Protein-Folding Prediction

By Jas Mehta

For decades, a fundamental question in biology remained largely unanswered: how do proteins fold? Proteins, large, complex molecules, play crucial roles in virtually every biological process within our cells. These building blocks, the workhorses of our cells, contort their amino acid chains into intricate 3D shapes that dictate their function. Unveiling these structures has been a slow and expensive endeavor, hindering progress in medicine, drug discovery, and our understanding of life itself.

Researchers have grappled with the challenge of deciphering protein structures using methods such as X-ray crystallography and computational modeling. However, these approaches often fell short in terms of accuracy and efficiency. Scientists and software developers using artificial intelligence (AI) concepts are creating powerful new tools to address this challenge. One example, called AlphaFold, was developed by the DeepMind subsidiary of Google’s parent company, Alphabet. AlphaFold represents a paradigm shift in protein structure prediction, building upon decades of research engaging with the intricate puzzle of protein folding, and leveraging the power of deep learning to achieve near-atomic accuracy in predicting 3D protein structures from amino acid sequences. (See the image below for an example of how researchers are computing protein structure from amino acid sequence data.)

Computing protein structure from amino acid sequence


This breakthrough has not only streamlined the process, reducing prediction times from months to minutes, but has also opened new avenues for drug discovery and biomedical research, promising to revolutionize our understanding of proteins and their functions within cells. This represents a monumental leap compared to traditional methods like X-ray crystallography, which can take months or even years. This breakthrough not only accelerates research cycles and slashes costs but also holds profound implications for fields ranging from medicine to materials science.

In the 14th Critical Assessment of Protein Structure Prediction (CASP), a biennial competition, AlphaFold achieved a staggering feat. It matched or surpassed the accuracy of experimental methods for a whopping 90% of proteins, showcasing the immense power of deep learning for this complex task. Historically, determining a protein structure could cost upwards of $100,000 and take months. AlphaFold slashes this time to minutes, with a projected cost per prediction of mere cents. This translates to significant cost savings and faster research cycles.

Designing drugs often hinges on knowing a protein’s structure. AlphaFold’s speed and accuracy streamline this process. A recent study used AlphaFold to identify a potential drug target for a baffling neurodegenerative disease, a process that would have taken significantly longer using traditional methods. Moving beyond snapshots, the next frontier is understanding how proteins fold, move, and interact within the cell. This will provide invaluable insights into cellular processes and protein function. Deep learning thrives on data. Integrating protein interaction databases, cellular environment data, and real-time folding kinetics will further enhance the accuracy and applicability of protein structure prediction. Open-source platforms like AlphaFold are making these powerful tools accessible to researchers worldwide. This fosters collaboration and accelerates scientific progress across disciplines.

The success of AlphaFold stands as a testament to the indispensable role played by the Protein Data Bank (PDB), a vast repository housing experimentally determined protein structures. Mr. Darnell Granberry, a distinguished machine-learning (ML) engineer at the New York Structural Biology Center, sheds light on the critical importance of open data in driving groundbreaking advancements in protein research. “The PDB contains nearly all of the protein structures that have been experimentally determined, and the fact that it’s open source is a major enabler of AlphaFold and other protein ML models,” remarks Mr. Granberry. “If we didn’t have it, I think we’d likely have been limited to in-house models developed at pharma/biologics companies on proprietary data.”

His insights offer a nuanced understanding of the symbiotic relationship between computational methods and protein research, emphasizing the transformative impact of accessible data on scientific innovation. Furthermore, Mr. Granberry eloquently articulates a foundational principle of biology, stating, “There’s that central dogma of biology: DNA to RNA, RNA to protein, protein to function. So basically, anything that you’re interested in, basically in any living thing, is going to be rooted in some sort of protein or complex of proteins, or collection of them that interact with each other.”

In his words, we discern a profound appreciation for the pivotal role played by proteins in shaping the essence of life itself, underscoring the fundamental importance of unraveling their structures and functions in driving progress across diverse realms of scientific inquiry.

In a recently published study, researchers used AlphaFold to predict the structure of a protein implicated in amyotrophic lateral sclerosis (ALS), a debilitating neurodegenerative disease. The predicted structure revealed a never-before-seen binding site, paving the way for the design of drugs that could potentially slow or halt disease progression. This exemplifies AlphaFold’s potential to revolutionize drug discovery, particularly for complex and previously untreatable diseases.


The chart above depicts the median accuracy of protein-folding predictions in the free-modeling category of the CASP competition over the years. As you can see, there was a significant jump in accuracy in 2018 and 2020, coinciding with the introduction of DeepMind’s AlphaFold systems. This dramatic improvement highlights the transformative power of deep learning in protein-folding prediction.

Deep learning has irrevocably transformed protein-folding prediction. As we delve deeper into protein dynamics and leverage the power of big data, the potential applications are truly boundless. From developing new medicines and biomaterials to a fundamental understanding of how life works at the molecular level, AlphaFold and its successors promise to usher in a new era of biological discovery.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

From Marine Biologist to Antarctic Explorer: Fay Couceiro’s Quest to Understand Microplastics

By Shruti Gosain

Navigating the challenges and discovering solutions for environmental health along with exploring the impact of tiny particles on Antarctica and beyond.

Close-up of Fay Couceiro with sunglasses, with the words "Seeing Microplastics."


Headshot of Fay Couceiro in Antarctica.

Fay Couceiro, whose journey has taken her from the shores of marine biology to the expansive landscapes of environmental science, is a biogeochemist who studies microplastics. She has traveled all over the world to understand how microplastics affect our environment. Her work took her from the Caribbean and Southeast Asia to Africa and the UK. However, one destination remained unchecked on her bucket list—the polar regions. Pushing her boundaries even further, she has recently ventured into the icy depths of Antarctica to understand how tiny plastic particles are impacting this remote corner of the Earth.




Ice-covered landscape in Antarctica.


But what exactly are microplastics, and why are they such a big deal?

We know that plastic is everywhere in our lives, from wrapping our vegetables to holding water. Since it was invented in the early 1900s, plastic production has skyrocketed. People worldwide buy a million plastic bottles every minute and use 5 trillion plastic grocery bags every year! The problem is, while plastics are convenient, they’re also harmful to our health and the environment. Plastic is lightweight, flexible, and long-lasting but here’s the kicker: plastic doesn’t just disappear. A plastic water bottle, for example, might break into smaller pieces over time, but it could take around 450 years or more to fully disappear. This means that the very first plastic items ever made are still around somewhere on Earth.

Microplastics are tiny pieces of plastic less than 5 millimeters in size that have become a widespread environmental concern. Microplastics are now found everywhere, from the Antarctic snow to remote deserts. Even smaller nanoplastics float in the air we breathe and the oceans we fish in. They can originate from the breakdown of larger plastic items due to exposure to environmental factors like sunlight and water. The primary materials making up microplastics include polymers like polyethylene, polypropylene, and polystyrene, which are commonly used in the production of various plastic products. Despite their size, microplastics pose significant threats to ecosystems and human health.

So, back to Fay’s Antarctic adventure. Recently, she got a chance to study microplastics in Antarctica on a Royal Navy ship, the HMS Protector. Contrary to expectations, the Antarctic summer wasn’t as freezing as one might imagine, with average temperatures hovering around 33–36°F (1–2°C). “It was the summer and it was not nearly as cold as you would think it would be. I actually went outside on deck in a thermal and a jumper some days. When there’s no wind it is about one degree,” says Fay.

Sunset on Antarctic coastline.


But despite the milder weather, it was an adventure nonetheless. The Royal Navy provided everything needed for the research, making it a unique opportunity. Here, she collected diverse data, focusing on pollutants like nutrients, heavy metals, and microplastics. However, collecting samples in Antarctica posed challenges. The collection process involved a meticulous balance of technology and simplicity. The water samples were obtained with buckets and bottles, but specialized tools such as plankton nets and sediment grabs were used to ensure accurate sampling of microplastics without contamination from the ship’s materials.

Now, why is studying microplastics so crucial, you ask?

Well, because they’re everywhere, and their presence raises concerns about their impact on wildlife and human health. These tiny plastics may seem insignificant, but their omnipresence is cause for alarm. Through her work, Fay hopes to shed light on the pervasive nature of microplastics and inspire action to mitigate their impact. So, the next time you unwrap a plastic package or sip from a disposable water bottle, remember Fay’s Antarctic adventure and the vital importance of understanding the hidden world of microplastics.

Microplastics are more than just small plastic!

Surprisingly, even though we produce millions of tons of plastic each year, we know very little about the health effects of microplastics. “The smaller the particle, the more damage it can do,” says Fay. Fay states that these microplastics can also carry chemicals from the environment, making them harmful when animals eat them. In aquatic invertebrates, the impact of microplastics is alarming. They contribute to a decline in feeding behavior and fertility, impede larval growth and development, elevate oxygen consumption, and stimulate the production of reactive oxygen species. Fish, too, face detrimental effects, including structural damage to the intestine, liver, gills, and brain. Microplastics can disrupt metabolic balance, alter behavior, and affect fertility in fish, with the severity of these consequences depending on particle size, dosage, and exposure parameters.

Penguins jumping off an iceberg in Antarctica.


Fay also found that bacteria stick to microplastics, creating a slimy layer called a biofilm. If that biofilm contains pathogens, it can harm marine life. She wants to figure out how much harm microplastics can cause and how to stop it. Understanding the intricate web of harmful effects caused by microplastics is crucial for developing comprehensive strategies to mitigate their impact on both human health and aquatic ecosystems.

Now, we cannot completely neglect plastics. Since their invention over a century ago, plastics have become part of our daily lives. “I genuinely don’t believe we will eliminate all plastic because it is a ridiculously useful material,” says Fay. But we make and use so much plastic that plastic pollution is now a big concern. While some plastics can be recycled, others pose real challenges to the recycling process. Of those plastics that are easy to recycle, few are considered feasible. Most are thrown into landfills, where they break down over time into smaller pieces. These have seeped into our oceans and waterways, so tiny plastic bits are showing up in some seafood. And when we wash fabrics made of plastics like nylon or polyester, plastic bits can blow out of our dryers, adding to air pollution. Scientists have found microplastics in human blood, lungs, guts, and feces. They’ve also been seen in breast milk!

Good and Bad Plastics

“So, what’s the concentration of microplastics that poses harm to either humans or ecology, and how close are we to that threshold?” Fay inquires. “Let’s say it’s 100 microplastics per liter that causes problems, and we’re currently at 50. How do we ensure we don’t reach 100? That’s a tremendously challenging question,” Fay adds. She stresses the importance of removing large plastics before they break down into microscopic particles, as oceanwide filtration would be impractical. Larger pieces of plastic in the sea or on land become brittle and gradually break down. This is due to sunlight, oxidation, or friction, or by animals nibbling on the plastic. This plastic breakdown process goes on forever, although the speed depends on the circumstances. There are beaches where you not only see large pieces, but also countless fragments, colored or faded, and the smallest pieces can no longer be distinguished from grains of sand.

Now, we know that we could never completely eliminate plastic use, and we shouldn’t try to. What’s interesting is that scientists often study bigger pieces of plastic because it’s easier, even though the small ones might be causing more damage. It is, therefore, necessary for us to understand the composition and recyclability of different types of plastics and how essential it is for effective waste management and environmental conservation efforts. There should be awareness about good and bad plastics in the community. Fay believes that when people know more about microplastics, they care more. She reminds us that simplifying the types of plastics we use and focusing on the ones we really need can really make a lot of difference. This care can lead to changes in rules and policies. “We have had engagement with policymakers and are working with our policy groups,” says Fay. Fay has talked to important people who make decisions, hoping to influence them with her research.

So, fixing plastic pollution isn’t as simple as just picking up trash. We need to understand all the ways plastic harms the environment and come up with smart plans to stop it.


What Does the Future Hold?

“We’ve seen a significant rise in Antarctic tourism over the past three decades, with the number of visitors doubling each decade. While this might initially sound impressive, it’s also a cause for concern. Managed properly, ecotourism can bring substantial benefits, especially if visitors become advocates for preserving Antarctica. However, if large cruise ships fail to follow regulations and leave behind pollutants like metals, microplastics, and sewage, it poses a serious problem. We need effective monitoring and enforcement to maintain the pristine condition of this fragile environment.”

–Fay Couceiro

International cooperation and collaboration are crucial in Antarctica, where tourism is increasing and environmental impacts are a concern. Microplastics harm Antarctic life by entering the food chain, affecting the health of organisms and making them less able to cope with climate change.

Seal on the ice in Antarctica.


Fay delved into ongoing research efforts, shedding light on the exploration of enzymatic breakdowns as a promising solution to the microplastic issue. “There are chemical methods available for eliminating plastics, but they tend to be costly and not very efficient, especially when dealing with microplastics,” says Fay. However, she emphasized the considerable challenge of scaling up these processes effectively. “We have enzymes that can eat plastic and separate them into their smaller monomers. But how do we do that on an industrial scale? And how would we do that with a mix of them? We can’t separate them out into the perfect laboratory conditions. So how do we scale that up?” asks Fay. Moreover, she also underscored the critical importance of monitoring human activities, particularly those associated with cruise ships, in delicate ecosystems like Antarctica. This interactive approach not only engages but also prompts reflection on our collective responsibility to safeguard these precious environments.

Fay hinted at exciting future endeavors, including a groundbreaking comparative study between the Arctic and Antarctic regions. Such an exploration promises to unveil crucial insights into how human activities impact these pristine polar environments. As we delved deeper into the conversation, it became evident that Fay’s passion lies in unraveling the intricate relationship between human actions and environmental health. She articulated a pressing need for a paradigm shift, urging us to move beyond short-sighted monetary gains and prioritize the long-term well-being of our planet.

But what exactly is at stake? Consider this staggering statistic: people worldwide purchase a million plastic bottles every minute, while a mind-boggling 5 trillion plastic grocery bags are consumed annually. These numbers paint a stark picture of our reliance on plastic convenience items. Yet, convenience comes at a cost—one that’s detrimental to both our health and the environment.

It’s a problem exacerbated by an industry that thrives on the production and distribution of plastics, raking in over $600 billion annually. This financial incentive fuels a cycle of consumption, production, and waste that threatens the very ecosystems we depend on. However, amid the grim realities, Fay’s work offers a beacon of hope. By unraveling the mysteries of microplastics and shedding light on their impact, she empowers us to make informed choices for a cleaner, healthier planet. Her optimism stems from the belief in humanity’s collective ability to address environmental challenges through collaborative efforts.

As we reflect on Fay’s insights, it becomes clear that the microplastic challenge isn’t just an isolated issue. It’s a symptom of a broader problem that requires urgent attention. It’s a call to action, urging us to rethink our consumption patterns, advocate for sustainable practices, and hold industries accountable for their environmental footprint. In the end, Fay Couceiro’s work serves as a reminder of our shared responsibility to safeguard the planet for future generations. It’s a reminder that by working together, we can pave the way towards a more sustainable and prosperous future.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or topics we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities, including our cross-sector Water Data Forum webinar series, which recently had a session on microplastics and AI.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Governing Smart Cities and the Ethical Considerations of Big Data

By Ken Ogata

From smartphones to surveillance cameras, to automatic doors and artificial intelligence, the cities we live in have become “smarter,” carrying the promise of productivity and modernization. While “smart” technology seemingly makes our lives easier, are we giving up the benefits of privacy and individualism?

In a new book, Governing Smart Cities as Knowledge Commons, edited by Brett M. Frischmann, Michael J. Madison, and Madelyn Rose Sanfilippo, experts in law, policy, and information science examine how we can properly govern “smart” cities through models based on ethical and social considerations, and information science.

With the increasing integration of technology into our daily lives, the amount of data and information that is gathered, stored, and analyzed by cities has skyrocketed.

“Residents are connected to each other and to governments and other organizations by fiber and wireless connections.” The authors of Governing Smart Cities as Knowledge Commons write in Part 1 of the book, “‘The people’ and their environments are rendered and represented digitally in the bureaucracies of public administration and in the dynamics of everyday life.”

As the role of Big Data becomes more important in city policy, data governance—the standards and regulation for the storage, usage, and disposal of data—has never been more relevant. Dr. Angie Raymond, who coauthored a chapter in the book and is a Professor of Business Law and Ethics at Indiana University, states that many cities in the United States lack the manpower and expertise to efficiently use the data collected.

“The problem a lot of cities are facing is that the skills required to use data are new,” Raymond said. “And unfortunately, cities are oftentimes well behind the curve on being able to find (well-trained) employees.”

Raymond added that many cities lack the infrastructure to store data for proper use later down the road. “The biggest issue for cities is oftentimes cities have been gathering data for a long time . . . they have a repository of data, which is oftentimes a Box folder with some security on it, and a lot of PDFs, which are incredibly difficult to be used.”

The authors also state that modern cities can get wrapped up in hype and adopt “smart” technology for the sake of modernization, not taking the time to consider what data it shares and collects and how to properly govern it.

The book notes that seemingly innocent examples of “smart” technology can have unintended consequences, such as an automatic door with a camera.

“What if the automatic door could identify people prior to opening the door? What if the automatic door could send an alert when an unauthorized person attempts to enter the building?” the authors ask in Part 4: Lessons for Smart Cities. “This requires new sensors, intelligence-generating tools and processes (identification), and automated actions . . . The camera-based system collects much more data than is needed, creating privacy risks that are easily overlooked or underestimated.”

To prevent cases like this, the authors of the book present the Governing Knowledge Commons (GKC) framework as a useful tool when evaluating the governance of smart technology. The book emphasizes the importance of comprehensive public knowledge in regard to data storage and collection, and the implementation of new smart technology across the city.

“We need to figure out a way that we can all use data to produce information, and then we’re sharing it amongst a larger community,” Raymond said. “Commons is just a fancy word for saying we all get together and we know the boundaries and have a set of rules.”

As an example of the GKC framework, Raymond brings up the Dewey Decimal system present in libraries across the country and how it could be used to set up a proper data governance topology for cities.

“It doesn’t matter what library you walk into, if you walk to the fiction section, you can find Stephen King, and (000) is the computer science section in every library all round the world,” said Raymond. “If we could ever develop an actual system where we were using similar variables with similar labels (for city data), we would be in a different place.”

Using the GKC framework as a foundation, the authors of the book provide a set of questions that can be used by administrative governments when considering the pros and cons of installing smart technology:

Closed-Circuit Television (CCTV) camera against the blue sky, with the questions “What data is generated?,” “Who has access to this data?,” and “Will the tool actually deliver what is promised?”
Graphic by Ken Ogata; original image from Pexels/Jan van der Wolf

In the book’s concluding chapters, the authors mention in Part 4 that proper data governance requires comprehensive public knowledge and also community members that are well informed and capable of taking action and voicing concerns about data collections and city projects. “Simply put, cities aren’t smart, but the people living and working in cities might be.”

In making sure that data governance is upheld and smart technology does not infringe upon the rights of citizens, Raymond urges those capable to make sure that their voices are heard. “Citizens need to understand that if you are in the room and you have a voice, there are probably three people not in the room who don’t have a voice.”

Cities themselves can only be as smart as the people living in them. Accountability lies not only in the hands of the experts, but also the larger city community, whose job it is to make sure that we still have a voice in our cities.

Get Involved

Those interested in the Governing Knowledge Commons (GKC) framework can access the official Workshop on Knowledge Commons Website for further explanations of the framework and future projects and events.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Data Centers for AI and Quantum Computing

By Jas Mehta

In the rapidly evolving landscape of technology, data centers stand as the backbone of our interconnected world. As demands for computational power, storage, and connectivity continue to surge, the data center ecosystem is undergoing a profound transformation. This blog post explores the interplay of emerging trends, seamlessly integrating artificial intelligence (AI), Co-Packaged Optics (CPO), Compute Express Link (CXL), and other cutting-edge technologies that are reshaping the very fabric of data centers.

Artificial intelligence has emerged as a central force propelling the evolution of data centers. The insatiable appetite for AI applications, from machine learning to deep learning, necessitates a paradigm shift in computational capabilities. Data centers are rising to the challenge by incorporating specialized hardware, such as Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs), to accelerate AI workloads. This shift towards AI-centric infrastructure not only redefines the computational landscape but also sets the stage for unprecedented efficiency and capabilities within data centers.

Enter Co-Packaged Optics (CPO), a transformative technology that promises to elevate the performance and efficiency of data centers. Traditionally, optical transceivers existed as separate entities from processors, posing challenges in terms of power consumption, latency, and scalability. Co-Packaged Optics integrates these components directly into the processor package, minimizing signal losses and optimizing data transfer within the data center.

This integration not only enhances bandwidth and reduces latency but also addresses critical concerns surrounding space and energy efficiency. As data centers grapple with the escalating demand for higher data rates, CPO emerges as a game changer, streamlining connectivity for optimal performance.

Simultaneously, Compute Express Link (CXL) has garnered attention as an open industry standard facilitating high-speed, efficient connectivity between diverse devices within data centers. CXL seamlessly connects Central Processing Units (CPUs), GPUs, and other accelerators, fostering a heterogeneous computing environment. This versatility is indispensable for data centers navigating the diverse landscape of workloads, including the intensive requirements of AI and high-performance computing (HPC).

Compute Express Link’s impact extends beyond improving data coherency; it fundamentally enhances communication between processors, promising a holistic improvement in overall system performance. The adoption of this standard is gaining momentum, signaling a shift in the architectural paradigm of future data centers.

As we envision the future of data centers, it is essential to consider the broader spectrum of transformative technologies.

Quantum computing, though in its infancy, holds immense promise in solving complex problems exponentially faster than classical computers. As it matures, quantum computing could potentially revolutionize data centers, offering unprecedented computational capabilities for certain workloads.

The future of data centers is a dynamic convergence of groundbreaking technologies, where AI, CPO, CXL, and other emerging trends seamlessly intertwine. As the demand for computational power continues to soar, data centers must not only embrace but actively integrate these innovations. In doing so, they can ensure scalability, efficiency, and optimal performance in the face of evolving technological landscapes. The journey towards the next generation of data centers is an exciting one, marked by transformative technologies that pave the way for a more connected, intelligent, and sustainable future.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

BlueGAP: A Community-Driven Movement Against Nitrogen Pollution

By Shruti Gosain

We all love the tranquility of our water bodies, but there’s a silent threat lurking beneath the surface. Nitrogen pollution! Nitrogen pollution is also called the hidden troublemaker of our water system. It’s not something we can see, but it’s a big problem for our precious water resources. Nitrogen pollution comes from natural processes and things we do, such as farming and industry. It comes in forms like ammonia, nitrate, and nitrite. While nitrogen is important for life, having too much of it in our water is a problem. One of the major drawbacks is the promotion of accelerated growth of algae and other aquatic vegetation. This excessive growth, fueled by the abundance of nitrogen, can result in harmful algal blooms that have detrimental effects on aquatic ecosystems. These blooms not only alter the balance of the ecosystem but also pose threats to the living organisms within it. What makes it worse is that it hits vulnerable communities the hardest. These are often people who already face challenges, and they rely on this contaminated water. That means more health problems, harm to the environment, and financial troubles. This, in turn, leads to more health problems, harm to the environment, and financial troubles for these communities. Nitrogen pollution becomes not just a hidden troublemaker but a pressing issue with far-reaching consequences.

It is said that recognizing a hidden threat is often the first vital step in dealing with it. The U.S. National Science Foundation (NSF) is taking a significant stride in addressing major global challenges such as climate, sustainability, food, energy, pollution, and the economy. According to Douglas Maughan, the head of the NSF Convergence Accelerator program, this initiative involves a range of approaches, including human-centered design, user discovery, team science, prototyping, storytelling, and pitch preparation.

The Convergence Accelerator program is focused on themed tracks. The Networked Blue Economy track is one of the most mature tracks, with a substantial $30 million investment to advance six research teams from Phase 1 to Phase 2, made in September 2022. This underscores the importance of the blue economy in addressing pressing ocean-related challenges, including plastic waste and coastal erosion.

About BlueGAP
One standout Phase 2 awardee is the Blue-Green Action Platform (BlueGAP) project, led by the University of South Florida. In a groundbreaking initiative to address nitrogen pollution and its impact on communities from the upper Mississippi River to the Florida Gulf, the BlueGAP project leveraged the innovative power of mixed-media art to communicate the environmental challenges. The project enlisted the expertise of graduate students from arts and humanities programs, empowering them to explore various storytelling avenues around nitrogen pollution. With creative freedom and access to stakeholders in Iowa watersheds, the resulting artwork seamlessly integrated with data and narratives on nitrogen pollution. As a Professor of English at the University of Iowa, Eric Gidal led a team of graduate students in creating a unique art exhibit in Iowa. This exhibit, called “Fluid Impressions,” combined sculptures, art books, and digital formats to tell stories about nitrogen pollution and inspire action. The intended audience included Iowans actively involved in water-quality issues, University of Iowa faculty and students, and curious members of the general public.

“I think the exhibit succeeded in calling attention to the problem of nitrogen pollution,” Gidal said, “connecting people to an evolving network of resources, and showcasing some very innovative work from talented young artists, writers, and scholars. I would also say that it successfully demonstrates the many benefits of truly cross-disciplinary projects, in this case connecting hydrology and engineering with ceramics, choreography, book arts, journalism, literary studies, and creative nonfiction to produce a meaningful engagement with the wider community.”

At the heart of the BlueGAP project lies a unique and powerful approach that has sparked a noteworthy reaction from communities—a fusion of storytelling and data-driven insights. Unlike traditional initiatives that either emphasize storytelling or focus solely on data dissemination, BlueGAP ambitiously intertwines narratives from communities grappling with daily challenges of nitrogen pollution with rigorous and relevant watershed impact data. What sets BlueGAP apart is its commitment to not only raise awareness through storytelling and provide data to the public but to catalyze tangible actions, particularly in the realms of policymaking and decision-making. The project stands out as a beacon of innovation, recognizing that the convergence of narratives and data can be a catalyst for positive change.

“One of the most unique things about this project is the way storytelling, focused on the first-hand experiences of communities confronted with nitrogen pollution on a daily basis, really lies at the heart of what BlueGAP is all about,” said Rebecca Zarger, a professor in the Department of Anthropology at the University of South Florida, and a co-principal investigator on the BlueGAP project. “Our purpose is to connect those with stories to tell with one another and with the most rigorous and relevant data possible about watershed impacts from nutrients. There are projects that emphasize storytelling and those that focus on bringing data to the public, but fewer organizations are leveraging the power of simultaneously connecting stories and data to action, in the form of policymaking and decision-making.”

BlueGAP brings together a diverse group of academic, nongovernmental, quasi-governmental, and community organizations to raise awareness about the nitrogen pollution crisis and its impacts. This initiative connects community organizations across watersheds, addressing economic and health challenges caused by nitrogen pollution. BlueGAP partners with frontline community organizations to explore various funding sources to ensure initiatives aimed at improving water quality and ecosystem health have the necessary resources.

BlueGAP’s core model focuses on local experiences and knowledge, highlighting the costs and benefits of actions at specific leverage points in nitrogen management. The overarching vision of BlueGAP is to accelerate the convergence of best practices for nitrogen management and, by extension, stimulate the Blue and Green Economies. This initiative focuses on four key objectives:

  • 1.  Advanced Human-Centered Design: BlueGAP places human-centered design at the forefront of its approach because solutions to pollution are most effective when designed with people in mind.
  • 2.  Storytelling and Science: By weaving storytelling with cutting-edge scientific evidence, BlueGAP identifies pivotal points for action, ensuring that facts resonate with the public.
  • 3.  Inclusive Educational Materials: Education is the cornerstone of change. BlueGAP is committed to creating inclusive educational materials that impact nitrogen management and engage communities.
  • 4.  Establish a Sustainability Plan: To ensure the longevity of its mission, BlueGAP lays the groundwork for a sustainability plan that will see its efforts continue well into the future.

So, BlueGAP is not just another environmental initiative; it is a dynamic, community-driven movement. It leverages the power of collaboration, communication, and innovation to tackle the pressing issue of nitrogen pollution. BlueGAP’s mission reflects on NSF’s commitment to supporting initiatives that demonstrate intellectual merit and broader impacts, recognizing that the health of our watersheds is vital for a sustainable and thriving future. With BlueGAP leading the way, the path to a cleaner, healthier, and more sustainable Blue Economy has become clearer.

BlueGAP Co-Principal Investigator Maya Burke says that in propelling the BlueGAP Academy forward, one standout stakeholder has played a pivotal role—Hillary Van Dyke, Director of Opportunity and Access at Impact Florida. Her impact reverberates through the Tampa Bay region, where she has been a driving force in introducing Black communities to the wonders of wild places. Her multifaceted contributions showcase the power of individual dedication and community engagement in advancing the goals of BlueGAP, aligning with the project’s commitment to inclusivity, environmental awareness, and positive change.

Through collaboration with community leaders in Iowa, Tampa Bay, and St. Croix, the project has learned that stories play a pivotal role in building trust and motivating collective action. By producing high-quality videos with American Sign Language (ASL) translation, BlueGAP aims to share diverse perspectives connected to nitrogen pollution. These stories, coupled with accessible water quality data, serve as compelling tools to engage and mobilize communities.

Role of Data
The project is actively building a qualitative database, intertwining personal narratives with water-quality metrics, to create a dynamic platform that not only informs but inspires meaningful action toward improved nitrogen management within and across watersheds. In essence, BlueGAP’s commitment to the simultaneous integration of storytelling and data-driven approaches marks a transformative shift in environmental initiatives, demonstrating the potential for a more comprehensive and impactful engagement with communities. With a strong focus on the Networked Blue Economy, this program is diving into areas such as water, agriculture, and community well-being. Let’s break it down!

Water: This program is all about improving how we monitor and manage water resources. That means cleaner water, better resource allocation, and sustainable practices—a win for everyone.

Agriculture: The Convergence Accelerator program brings experts together to create data-driven solutions for agriculture. Weather patterns, soil conditions, and crop performance all help farmers make smarter decisions. Think higher productivity, less waste, and greener practices!

Community: In our neighborhoods, data and information matter, especially for healthcare, education, and our overall quality of life. This means healthier living, improved education, and easier access to community services.

So, what’s the connection between data systems and these critical areas? Well, it’s all about making things work together. Maya Trotz, Principal Investigator of BlueGAP, says that storytelling has been a key way to bring together these technical threads in ways that build local community engagement.

“Empowering communities to take actions on any issue requires a certain level of trust and willingness to work towards a common goal—for BlueGAP, that is improving how we manage nitrogen within and across watersheds,” said Trotz. “Working with community leaders in Iowa, Tampa Bay, and St. Croix, we quickly learned that stories were critical for building trust. When coupled with accessible water-quality data, those stories could really motivate others to take action. So, we are producing high-quality videos with ASL translation to tell stories of people who are connected to nitrogen pollution from many different angles. We are building a qualitative database with these stories and connecting that to our water-quality data.”

By bringing these elements into sync, the Convergence Accelerator program aims to create positive changes, not just for the Networked Blue Economy but for anyone who relies on clean water. The program’s approach is all about connecting the dots and using data to drive solutions in these vital sectors. That’s not just a win; it’s a win-win for everyone involved. Also, bridging the gap between scientific knowledge and public engagement is the impactful documentary film, “Harm in the Water,” led by Tiara Moore, CEO of Black in Marine Science. It serves as a powerful tool for BlueGAP, translating technical information into an accessible format. This film emerges as a beacon, engaging citizens and making complex data more understandable.

BlueGAP and MBDH
“Water quality is a key topic of concern to our communities in the Midwest and Great Lakes regions,” said John MacMullen, Executive Director of the Midwest Big Data Innovation Hub, who is also a member of BlueGAP’s Advisory Board. “It impacts human and animal health across the spectrum from rural to urban populations, and we know that water crosses state boundaries, leading to impacts elsewhere, such as the Florida Gulf Coast. We think BlueGAP’s innovative storytelling approach is a great way to raise public awareness of water-quality challenges and how they impact local communities.”

The shared interests between the BlueGAP and MBDH communities provide opportunities for future collaboration, both in storytelling and other programmatic activities, such as the Water Data Forum, a cross-sector venue for sharing best practices and new innovations in water data. The next session of that webinar series will be in April 2024, and will be focused on data and AI for contaminant remediation.

Conclusion
BlueGAP stands at the forefront of environmental initiatives, unraveling the complexities of nitrogen pollution through a remarkable fusion of storytelling and data-driven insights. This project exemplifies a commitment to tackling global challenges innovatively. The project’s holistic model, encompassing local experiences, human-centered design, and inclusive educational materials, positions it as a community-driven movement making tangible strides. As BlueGAP continues to address nitrogen pollution, it not only enhances water-quality understanding but also empowers communities, exemplifying the potential of convergence in shaping a sustainable and thriving future for our watersheds.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities, including our cross-sector Water Data Forum webinar series.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Reshaping Agriculture in a Changing Climate with Insights from Predictive Analytics

By Shruti Gosain

We’re in a time where technology is moving faster than ever. In an age of rapidly advancing technology, the intersection of data science, climate science, and agriculture is producing game-changing results. Predictive analytics, a cutting-edge approach to data-driven forecasting, is revolutionizing our ability to foresee and respond to the challenges posed by a changing climate. It’s like having a crystal ball that helps us predict and prepare for the problems that impact society in different ways due to climate change.

The Power of Predictive Analysis in Climate Science

In the world of climate science, researchers use big sets of data from tools like satellites and weather stations. With the help of super-smart computer programs, they can make predictions about things like extreme weather and long-term climate changes. These predictions help us understand what’s happening with the Earth’s climate and get ready for changes like heat waves and storms.

Satellites and weather stations collect a huge amount of data about the weather and climate. Then, with the help of artificial intelligence and machine learning, scientists can predict things like wild weather events, seasonal changes, and long-term shifts in our climate. Now, why is this exciting? Well, think about it: These predictions are like knowing the future, but for the weather. Farmers can use this information to figure out when to plant their crops. If they know there will be a dry spell, they can be ready with extra water. And when we’re talking about big events like hurricanes or floods, predictive analytics helps us get ready—by strengthening our buildings or planning better emergency responses. The case studies in the table below this article illustrate this in more detail.

Predictive Analytics Reshaping the Future of Agriculture

Now, let’s talk more about farming. Farmers rely on the weather and the climate to grow their crops. But with increasing heat and more frequent droughts impacting yields in many growing areas, things are getting tricky. Predictive analytics steps in to help. It looks at large amounts of information like past climate data, how healthy the soil is, and how different crops are doing. Then, it tells farmers when to plant, what to plant, and how much they’ll get when it’s time to harvest. This is what’s called “precision agriculture,” where we use data to be more precise in how we grow food.

Agriculture is inherently dependent on climate, making it one of the sectors most vulnerable to climate change. Predictive analytics offers a lifeline to farmers. By analyzing historical climate data, soil health, and crop performance, predictive models can provide insights into optimal planting times, crop selection, and yield projections. The data-driven decisions enabled by predictive analytics reduce risks, enhance resource management, and increase productivity. For example, in regions facing water scarcity, predictive models can suggest the most efficient irrigation strategies to minimize water wastage. This technology is revolutionizing precision agriculture, optimizing the use of resources and minimizing environmental impact.

Imagine a farmer in a place where it’s superhot and there isn’t much rain. Predictive analytics tells them the best time to plant their crops and how much water to use so they don’t waste any. This means more food on our plates and less waste. So, it’s not just about scientists making cool predictions; it’s about using those predictions to make our world safer and smarter. It’s like having a heads-up about the future and, with that, we can plan better, adapt to change, and protect our planet. Climate science and predictive analytics are like our secret weapons against the unpredictable weather and they’re here to save the day!

Let’s look at a real-life example. In California’s wine country, vineyard managers use predictive analytics to know when to prune the vines, when to water them, and when to pick the grapes. This makes their vineyards strong and good for the environment. The integration of predictive analytics in climate science and agriculture is not just a forward-thinking idea; it’s a necessity in a world facing escalating environmental uncertainties.

Future, Necessities, and Challenges in the Path to Predictive Analytics Mastery

While predictive analytics holds immense promise, challenges exist. The accuracy of predictions depends on the quality and quantity of data, which can be influenced by factors such as data collection infrastructure and access to satellite technology. Additionally, ensuring that predictive models are accessible to farmers, particularly in developing regions, is a critical challenge.

As we look to the future, addressing these challenges is paramount. The integration of predictive analytics in climate science and agriculture is not a luxury but a necessity. It equips us to tackle the evolving climate crisis with proactive strategies, ensuring food security, environmental sustainability, and resilience in the face of uncertainty. Moreover, fostering collaboration between researchers, policymakers, and technology innovators will be essential in harnessing the full potential of predictive analytics to address the pressing challenges of our times.

Conclusion

Predictive analytics is the bridge between knowledge and action in the realms of climate science and agriculture. As we continue to refine these predictive models and make them more accessible, we inch closer to a world where our responses to climate change are not reactions but anticipations, where agriculture adapts seamlessly to shifting climate conditions, and where we collectively move towards a more sustainable and resilient future.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or topics we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Predictive Analytics Case Studies

Precision Farming for Sustainable Agriculture
Issue: In a region experiencing increasingly erratic weather patterns, farmers faced the daunting task of optimizing crop production while conserving resources and adapting to changing conditions. [Sources: 1, 2]    Solution: Predictive analytics tools were used to analyze historical climate data, soil quality, and crop performance. Using machine-learning algorithms, these tools forecasted ideal planting times and crop varieties as well as recommended precise irrigation schedules. By relying on data-driven decisions, farmers were able to enhance productivity, conserve water, and reduce the environmental footprint of their operations.  
Hurricane Tracking and Preparedness
Issue: Coastal communities were grappling with the increasing frequency and intensity of hurricanes, which necessitated better preparation and response strategies. [Sources: 1, 2]  Solution: Predictive analytics models were developed to track and predict hurricane paths and intensities. These models integrated data from satellites, weather stations, and historical hurricane data. The predictive analytics system provided more accurate forecasts, allowing authorities to issue timely evacuation orders, prepare emergency shelters, and allocate resources effectively. This resulted in improved safety for vulnerable communities during hurricane events.
Climate-Resilient Urban Planning
Issue: Urban areas were facing the dual challenge of population growth and climate change, leading to increased vulnerability to extreme weather events and flooding. [Sources: 1, 2]Solution: Predictive analytics played a pivotal role in urban planning. By analyzing climate data and topography, predictive models identified flood-prone areas and forecasted future vulnerabilities. Urban planners used this information to make informed decisions about infrastructure development, flood defenses, and emergency response plans. This proactive approach ensured that cities were better equipped to handle extreme weather events and protect their citizens.

MBDH Summer Workshops: Opening Doors to Data Science Education

By Ken Ogata

Ferry on Lake Michigan.


As the ferry boat steadily cruised over Lake Michigan, it marked the halfway point of Midwest Big Data Innovation Hub (MBDH) Outreach and Engagement Specialist J.D. Graham’s journey, which spanned thousands of miles and multiple states. Throughout the summer of 2023, Graham helped organize and co-lead three data science education workshops, collaborating with colleges across the Midwest to inspire both students and educators alike. Each was funded, in part, by the MBDH Community Development and Engagement Program. The workshops aimed at educating students about data science, especially communities often left out of the gated walls of higher education.

Graham stresses the importance of being there in person, and not just working remotely from his home in Illinois. “It really does matter to be there. To see that institution, the academic culture, their leadership . . . make the little conversations with people you don’t even know,” Graham said. “But the moment I heard it could exist, I was super excited to be able to do that. I like to travel.”

Prior to his position at the MBDH, Graham worked as an educator for 21 years, gaining experience with students from elementary school through college. This included teaching at the elementary and secondary levels as well as being a life coach for high school and college students at Kankakee Community College’s Upward Bound program. There, Graham worked on programs preparing at-risk students for college, further expanding his knowledge of learners’ needs across educational stages. Graham states that this broad classroom experience across student populations came in handy when facilitating the recent data science workshops.

“I have 20-plus years of reading a classroom to know what confusion, exhaustion, frustration, and success looks like,” Graham said. “If you aren’t used to dealing with those age ranges, by the time they will tell you that they will be telling you in actions, not words.”

The first workshop was in partnership with Central Michigan University and local school districts, with the goal to raise awareness of data science as a career path, especially for students who had not been exposed to this field before. The workshop introduced the field of data science through activities with R software and analyzing real-life datasets. While data science may be an exciting topic for many, Graham and his team realized that teaching teens about it was a delicate process—one that required building relationships with the students and making sure that the pace was just the right speed.

“If you make it an exciting, entertaining version of science, then you can sneak in the more difficult and frustrating parts of science,” Graham said.

The process of building trust with the students was not limited to the classroom either.

“We actually drove to their homes to pick them up to bring them to school. And during those periods of time, it’s not silence. It’s chatter. It’s talk,” said Graham. “They’re looking for a connection and these are the openings you use to click with the kids.”

As an educator, Graham is more than aware of the hurdles that exist in higher education, especially those in minority communities. “Most of us probably experience imposter syndrome, but these students have it on level 10. The moment they step in, they feel like outsiders.”

For Graham and his team, it was not only crucial to let the students see data science as a possible future for them, but also higher education in general. Throughout the workshop, Graham and his team brought in university tour guides and a financial aid counselor to help introduce the students to federal financial aid through the Free Application for Federal Student Aid (FAFSA) form.

“It’s so important because this face-to-face connection with people is the true boots on the ground, it’s how you change ideas, and how you build memories and experiences that will last a lifetime,” Graham said. “It lowers those barriers of entry and allows them to know that this is an accessible institution, and it’s right here in my neighborhood.”

Road through the Countryside.


The second workshop, in collaboration with St. Catherine University in Saint Paul, Minnesota, shared a similar goal to the first workshop. The five-day-long STEM academy was on-site at St. Catherine University and helped middle school girls in the local community engage with science through coding, rocket experiments, and 3-D printers. But on top of the activities planned for the kids, the workshop aimed to bolster the idea of Women and Girls in STEM, and allow children to envision opportunities that seemed unattainable to them.

“Most of the students I talked to said over and over ‘I just didn’t even know this existed or that this was a possibility,’” Graham said. “Allowing them to dream, to imagine themselves there. Maybe it’s not going to be in data science. But now it brings in whole new areas of study they’ve never even considered.”

A third MBDH workshop, the Workshop on Data for Good for Education (D4G4ED), was in collaboration with Trinity Christian College near Chicago and was primarily for educators and graduate students interested in exchanging ideas regarding teaching practices about data.

“Part of my job was to find people who not only cared about social good, and how to teach social good, but I also wanted to bring together a unique group of people with diverse backgrounds, so that they could learn from each other . . . to meet with professionals and passionate thinkers who they’d never have the chance to collaborate with on their own,” Graham said. He added, “Where else could a graduate student, a professor of Africana Studies, a virtual data viz instructor, and a data manager for the Department of Defense all meet up and discuss teaching data science for social good?”

The D4G4ED workshop was not only a place for educators alike to interact with each other and share ideas, but also aimed to challenge stereotypes and barriers that exist in certain fields of study in higher education. For Graham and his team, it was imperative that the workshop was not closed off to people who felt like they lacked the technical skills for data-related education, but to unite people under the idea of data science.

“[The] program was all about getting these diverse individuals whose communities, probably more than most, care about social causes and show them that data science can be used to promote and amplify those causes that they care about,” Graham said.

Graham also mentioned that the workshop was a great way to build relationships with his peers and noted how the workshops led to personal growth for him as well.

“Whenever I get to meet new people, whether it be professional or social, it allows me to get to see new tools and how they’re used, so I can incorporate them into my toolbox,” Graham said. “Meeting new educators, you learn new techniques, but just as importantly: meeting new students from new backgrounds. With different life experiences, I have learned so much from them as well.”

Through these workshops, Graham worked to demystify higher education and the field of data science. Graham’s work echoes the need for continued work towards breaking down the barriers that prevent many underrepresented groups from participating in academia.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or data science education projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities, including our Data Science Student Groups Community webinar series.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

New NSF awards drive the future of quantum computing

By Jas Mehta

Welcome to the realm of quantum computing, where the ordinary rules of the digital landscape no longer apply. In recent years, the burgeoning field of quantum computing has sparked a transformative revolution in computational power, promising to reshape industries and unlock new frontiers in technology. In light of this, there is an initiative aiming to propel quantum information science and engineering (QISE) into a transformative future, led by The National Science Foundation’s (NSF) ExpandQISE initiative. This strategic program facilitates collaboration between QISE Centers and academic institutions, transcending conventional scientific pursuits and fostering groundbreaking exploration. Further aiding the development, two recent awards made in the Midwest region by NSF in this program illustrate the diverse applications of this new technology.

Now, let’s dive into the story of a university that gained acclaim for its research in using nanodiamond quantum sensors for the enhancement of biomass pretreatment. The success of Southern Illinois University in Edwardsville (SIU-E) can be attributed to the presence of a team that is engaged in pioneering research. Their focus on using nanodiamonds, requiring advanced microscopes for observation, to investigate the conversion of common flora into a carbon-neutral biofuel aligns with broader environmental goals. This endeavor positions SIU-E scientists as modern luminaries equipped with cutting-edge investigative instruments. The adaptation of an advanced microscope to accommodate nanodiamonds as sensors resembles the meticulous work of detectives tracing evidential trails. These nanodiamonds, through their quantum properties, serve as sensitive probes capable of monitoring real-time alterations in plant materials. This application offers a unique insight, enabling the forecasting of the future of biofuel production. Nanodiamonds function as sensors by exhibiting quantum properties, such as nitrogen-vacancy centers, allowing for precise detection and analysis of changes at the nanoscale level. This innovative initiative extends beyond exploration; it establishes an institution where prospective scientists are educated in harnessing the remarkable capabilities of quantum science to aid in preserving and rejuvenating our planet.

The next award we’ll explore is Marquette University’s recognition for their research in quantum molecular dynamics, specifically focusing on its application to quantum computers. Marquette University, in collaboration with Los Alamos National Laboratory, received their grant from the Office of Multidisciplinary Activities (MPS/OMA) and the Technology Frontiers Program (TIP/TF) of the NSF. Their scientists use quantum computers to uncover the hidden world of atoms and molecules, providing a microscopic view of entities so minuscule that their existence seems improbable. The project delves into three pivotal areas. Firstly, it focuses on the development and applications of the Quantum Annealer Eigensolver (QAE) algorithm, pivotal for unraveling the rotational-vibrational spectra of molecules and illuminating chemical reactivity. Secondly, the project delves into quantum molecular dynamics simulations on QAE, using the quantum differential equations (QDE) algorithm to explore the intricate realms of molecule and surface phenomena. Lastly, the project ventures into theoretical studies, delving deep into coherent control of molecular eigenstates with a spotlight on QISE applications.

The evolution of quantum science experiences a profound surge through the concerted efforts of SIU-E, Marquette University, and the other QISE recipients, envisioning a future where commonplace flora evolves into sustainable energy sources. This visionary trajectory transcends conventional limitations, promising a sustainable future where quantum scientists unlock unprecedented possibilities.

To better understand the context in which these new innovations could be applied, we spoke with Santiago Nuñez-Corrales, PhD, about the strategic vision for quantum computing at the National Center for Supercomputing Applications (NCSA), housed at the University of Illinois at Urbana-Champaign. In his role as a research scientist and quantum lead at NCSA, Nuñez-Corrales is navigating the intricate interplay among quantum computing platforms, algorithms, problems, and human practices crucial for effective problem-solving, attempting to chart a pathway for the seamless integration of high-performance computing (HPC) and quantum computing (QC). NCSA is leveraging its expertise and proficiency in HPC to democratize quantum computing across scientific domains, ensuring accessibility, efficiency, and impact.

Three pivotal platforms emerge: Delta, Nightingale, and HOLL-I. Delta, succeeding Blue Waters, is a leading dedicated graphics processing unit (GPU) supercomputer, beckoning researchers to explore the efficiency of GPU system architecture in data analysis. This computational powerhouse hosts an array of resources, including 124 central processing unit (CPU) nodes, 100 quad A100 GPU nodes, and 100 quad A40 GPU nodes, among others. Researchers harnessing Delta can delve into intricate simulations in computational archaeology and digital agriculture, capitalizing on the system’s non-POSIX file system, modern file system benefits, and enhanced interfaces for widespread accessibility.

Nightingale, a secure and user-friendly HPC cluster, alleviates compliance burdens for research teams handling sensitive data, particularly in healthcare contexts. Researchers accessing Nightingale benefit from a secure computing environment managed by experts, facilitating focused research devoid of concerns about data compliance or security.

Concurrently, HOLL-I emerges as an innovative machine-learning capability at NCSA, boasting the Cerebras CS-2 Wafer Scale Engine. Offering extreme-scale machine-learning prowess, HOLL-I complements resources like Delta and HAL, efficiently facilitating large-scale machine-learning tasks. Using shared project storage on Taiga, a multiplatform file system, HOLL-I distinguishes itself through unparalleled processing speed, serving as an invaluable asset for researchers engaged in intricate machine-learning endeavors.

The plot thickens with the introduction of Clowder 2.0, an open-source data management framework, broadening its reach to a wider contributor base through the revision of core components. Its adaptability and user-friendly interface streamline data management and collaboration, empowering researchers across diverse scientific domains to expedite experimental science. Simultaneously, the transition from iForge to vForge denotes a strategic pivot aimed at streamlining operations for Industry Partners via virtual machines. Harnessing NCSA’s Radiant platform, vForge, an efficient successor to iForge, adopts virtual machines to optimize resource utilization and scalability. This transition allows NCSA to allocate on-site resources for larger projects while enhancing data accessibility across NCSA clusters through streamlined data migration to Taiga.

The climax of this saga materializes as NCSA collaborates with NVIDIA to introduce supercharged quantum processing units, catapulting the organization to the vanguard of quantum computing. Quantum computing will grow with previously unheard-of speed and precision in the future, transforming whole sectors and resolving challenging issues that were previously thought to be unsolvable. This will ultimately change the fundamental foundation of scientific research and technological innovation. As we transition from pioneers to witnesses of an ever-evolving landscape, the upcoming generation stands on the brink of a quantum revolution. As Santiago Nuñez-Corrales mentions, “We are the first generation of quantum people that are not really quantum. People involved in quantum computing in the next 5 years are going to be the first really quantum computing people.”

Get Involved

Contact the MBDH if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

NSF-Funded Hubs Partner to Develop the Water-Energy Nexus Open Knowledge Network

By Kimberly Bruch, San Diego Supercomputer Center Communications

The National Science Foundation (NSF) has funded a three-year cooperative agreement award of $1.47 million to create the Water-Energy Nexus Open Knowledge Network (WEN-OKN). This project involves impactful work across the West and Midwest Big Data Innovation Hub regions.

NSF logo.

“We are excited to bring together a team of partners with diverse backgrounds and representing multiple sectors, to develop WEN-OKN. It will connect data from vital water and energy systems, and help answer complex questions at the water-energy nexus,” said Principal Investigator (PI) Lilit Yeghiazarian, a professor of environmental engineering at the University of Cincinnati. “ WEN-OKN will become an integral part of critical national data infrastructure.”

The WEN-OKN has two primary goals: 1) create a knowledge graph that interconnects water and energy data throughout the nation and 2) explore ways to mitigate issues that evolve within these connections. The datasets being integrated into WEN-OKN include databases from the United States Geological Survey (USGS), National Oceanic and Atmospheric Administration (NOAA), Department of Energy (DOE), United States Environmental Protection Agency (USEPA), Federal Emergency Management Agency (FEMA), Department of Transportation (DOT), National Aeronautics and Space Administration (NASA), and the United States Army Corps of Engineers (USACE).

West Hub’s Ilya Zaslavsky, who is the director of the Spatial Information Systems Laboratory at the San Diego Supercomputer Center (SDSC) at UC San Diego, is a co-principal investigator along with the Arizona State University’s Center for Science, Technology and Environment Policy Studies Director Eric Welch.

The Midwest region is represented by PI Yeghiazarian as well as two co-PIs: University of Cincinnati’s Head of Department of Computer Science, College of Engineering and Applied Science Justin Zhan and Siddharth Saksena, who is an assistant civil and environmental engineering professor at Virginia Polytechnic Institute and State University (Virginia Tech).

“One of our key technical goals with WEN-OKN is to develop a unified semantic and spatiotemporal framework and create services for extracting energy- and hydrology-specific entities and spatial relationships from multiple databases,” Zaslavsky said. “Integrating these data into federated knowledge graphs will help multiple agencies to get answers to regulatory and policy questions for enhanced water and energy resilience.”

“This work is critical to the Midwest region of the U.S.,” said John MacMullen, Executive Director of the Midwest Big Data Innovation Hub. “The connections between water and energy in the Great Lakes region are key drivers for water quality, climate resilience, and agriculture. We are excited to see the impact this work will have on integrating knowledge from disciplines that are deeply connected but often isolated in specialized domains and repositories.”

The WEN-OKN has been funded by the NSF (award no. 2333726).

Meet the MBDH Fall 2023 science communications interns

For Fall 2023, the Midwest Big Data Innovation Hub (MBDH) has three new science communications interns joining the team to help tell the stories of people and data science projects in the Hub’s 12-state region. The interns will learn about the range of activities and communities the MBDH is involved in, will receive mentoring, and will have opportunities for career development. Below are details on the wide-ranging backgrounds and interests the students bring to the MBDH community.

Shruti Gosain

Shruti Gosain is joining MBDH as a Science Communications Intern this semester. She is a first-semester student pursuing a Master’s degree in Information Management in the School of Information Sciences at the University of Illinois at Urbana-Champaign. Shruti’s passion lies in working with data to generate innovative insights. She firmly believes that well-structured data, rather than raw data itself, holds the power to drive innovation.

Working with data is where Shruti thrives, and she is enthusiastic about diving deep into data analysis. Additionally, she possesses a strong inclination for writing and expressing her ideas. During her undergraduate years, Shruti had the privilege of representing her college in numerous debating tournaments, further fueling her passion for articulating her viewpoints and engaging in meaningful discussions. She finds a unique thrill in sharing thoughts and participating in intellectual exchanges. As a Science Communications Intern at MBDH, Shruti views this role as an ideal opportunity to blend her data-driven and communication skills.

“I am learning to learn,” says Shruti. She believes that there is always something to learn from various walks of life. What resonates most with Shruti about MBDH is its mission to enhance the data ecosystem through the promotion of strong networks encompassing academia, industry, government, and various organizations. She is eager to learn about different things and contribute by writing articles on diverse research topics.

In a nutshell, Shruti is thrilled to start on this journey, eager to contribute to its mission while refining her skills and expanding her knowledge. She looks forward to a semester filled with exciting opportunities and personal learnings!

Jas Mehta

Jas Mehta is joining MBDH as a Science Communications Intern for Fall 2023. He is currently pursuing a Master of Science in Information Management degree with a specialization in Data Science and Analytics at the University of Illinois at Urbana-Champaign, with expected graduation in May 2025.

In the realm of artificial intelligence (AI), Jas Mehta’s passions are directed towards the domains of learning, deep learning, and data science, which have captured his interest due to their wide-ranging applications and profound significance across diverse industries and professions; his professional background, encompassing roles such as Data Science Engineer at CWD Innovations and Machine Learning Engineer at Reliance Jio, has only deepened his commitment to these fields. These hands-on experiences have equipped him with invaluable skills and profound insights, positioning him as a catalyst for innovation and transformation within the realm of data science.

Jas’ pursuits are firmly anchored in exploring the vast potential of data-driven solutions to address pressing healthcare challenges. Whether it involves using data for predictive diagnostics or optimizing healthcare operations, he steadfastly believes that the synergy between data science and healthcare can unlock groundbreaking insights and innovations. He says, “Data is not just a collection of facts and figures; it’s the heartbeat of innovation, the foundation of informed decision-making, and the key to unlocking a brighter future.”

As Jas sets sail on his exciting voyage with the MBDH, he eagerly anticipates diving into the dimensions of research and storytelling. His inspiration flows from the opportunity to partake in a multitude of projects and narratives that possess the power to “let the data speak,” creating concrete impacts, enhancing awareness, and fostering positive societal change.

Ken Ogata

Ken Ogata is joining MBDH as a Science Communications Intern this semester. He is a sophomore at the University of Illinois at Urbana-Champaign studying Statistics with a minor in Computer Science.

As a newcomer to the Midwest, Ken believes that working at the MBDH will give him insight into the interconnected system of the Midwest states and how data plays a role in bringing it all together.

Ken is pursuing a career in data science and has spent the last two years exploring the intersection between data, computers, and everyday life. He hopes that his contributions to the MBDH will not only be a learning experience for him, but also communicate how crucial data and computer systems are to the greater Midwest.

“It’s hard to keep track of all the cool advancements our state is making, especially given how fast the world is moving nowadays,” Ken said. “I really want to learn more about my prospective career, and I think the best way to learn is to write about it.”

“I am delighted to welcome our three new Science Communications Interns, Shruti, Jas, and Ken, to the Midwest Big Data Innovation Hub for the Fall 2023 semester,” said J.D. Graham, Outreach and Engagement Specialist for the MBDH. “Having met them, I am excited about the unique knowledge sets, interests, and perspectives they each bring to the Hub.”

“Each intern has their individualized strengths. Shruti’s passion for structured data analysis paired with her communication talents makes her well-suited to translate complex topics. Jas’ professional experience in AI and hands-on engineering roles gives him a unique lens for conveying how data drives innovation. And Ken’s emerging perspective as a newcomer to the Midwest region will help broaden our narratives about how data connects communities. Their fresh insights will help to expand the reach and impact of the Hub’s storytelling as they showcase the diverse ideas from the Midwest that connect us all to data science.”

“Over the past two years, the MBDH intern program has been extremely well received by the regional data science community, NSF, and the interns themselves,” said John MacMullen, MBDH Executive Director. “We look forward to working with Shruti, Jas, and Ken this year as they help tell the stories of our regional community and develop their own skills and interests.”

The MBDH’s community-convening work continues in fall 2023, including multiple webinar series: the Collaboration Cafe, Midwest Carpentries Community, and Data Science Student Groups series, and the Water Data Forum, all open to participation from people across the region.

Get involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in our activities, which include a data science student community.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Building CI Capabilities with the Minority Serving – Cyberinfrastructure Consortium

By Aisha Tepede

The Minority Serving – Cyberinfrastructure Consortium (MS-CC) is an NSF-funded effort that promotes advanced cyberinfrastructure (CI) capabilities through collaboration with Historically Black Colleges and Universities (HBCUs), Hispanic-Serving Institutions (HSIs), Tribal Colleges and Universities (TCUs), and other Minority-Serving Institutions (MSIs) by using data, research computing, teaching, curriculum development and implementation, collaboration, and capacity-building connections among institutions.

The MS-CC is a vibrant and growing community of information technology (IT) professionals, campus leaders, faculty members, researchers, and students from across the nation’s HBCUs, TCUs, HSIs, and the broader community of MSIs. They are also joined by colleagues and leaders from regional and national organizations.

The main goals of MS-CC include increasing access to CI resources, enhancing interactions and effectiveness among researchers and CI professionals, and providing resources for professional and career development throughout institutions serving underrepresented students. MS-CC’s goals allow for growth and learning by advancing CI for research and education across diverse fields and communities.

In the past year, MS-CC has hosted multiple free CI and cybersecurity workshops at various universities, such as North Carolina A&T State University, Salish Kootenai College, Jackson State University, Claflin University, and the University of Maryland Eastern Shore. Topics ranged from the importance of CI on college campuses, access to open-source security tools, documented best practices for campus infrastructure, and hands-on workshop experience with IT leadership and staff. Along with workshops, MS-CC had the opportunity to present at the 2022 National HBCU Week Conference in Washington, D.C. to bring awareness to advancing CI for HBCUs.

MS-CC participant groups within
the 12-state MBDH region
• Chicago State University (IL)
• Fond du Lac Tribal and Community
  College (MN)
• Turtle Mountain Community College (ND)
• Cankdeska Cikana Community College
  (ND; formerly Little Hoop Community
  College)
• Sicangu Lakota Treaty Council (SD)

MS-CC recently hosted its first Annual Meeting for its community, and first Student Hackathon for students attending HBCUs and TCUs, in May. Hosted in partnership with Internet2 and with funding support from the National Science Foundation (awards #2137123 and #2234326), the events created a place for networking opportunities, community bridging, and student recognition.

The MS-CC community is built on lifting each other up and growing together. When joining the MS-CC, individuals become part of a vibrant community where they can collaborate, receive support, and advocate for their collective needs.

Joining the MS-CC as a participant is simple, quick, easy—and free! Fill out this form, join the mailing list, and stay informed about upcoming meetings and activities. MS-CC participants can also get involved by joining a committee or working group. Registration is open for a virtual orientation for prospective committee and working group members on Sep. 12 at 4 p.m. ET.

Get Involved

Looking at upcoming MS-CC events or activities, the MS-CC hosts monthly All Hands Meetings on the fourth Thursday of each month at 12 p.m. ET. It’s a great way to stay informed about upcoming workshops, webinars, events, the latest activities, and opportunities for collaboration, with their next meeting being on Sep. 28, 2023. Zoom details can be found here, along with recordings of past All Hands Meetings.

The MS-CC also hosts Cyberinfrastructure (CI) Plan Community of Practice monthly calls for IT leaders, staff, faculty, and/or others leading, interested in, or contributing to the development of CI Plan documents for their campus.

The MS-CC CI facilitation team and several leadership board members will be participating in the 2023 Internet2 Technology Exchange Conference from September 18–22, 2023. They are hosting the Science DMZ and Networking for All workshop on Monday, September 18, and giving a presentation titled “Cyberinfrastructure Advancement Designed by and for HBCUs and TCUs” on Wednesday, September 20.

Future cyberinfrastructure and cybersecurity workshops at HBCUs and TCUs, as well as additional communities of practice for MS-CC participants, are being planned and will be announced on their website in the coming months.

Contact the MBDH if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

From I, Robot to AIFARMS; AI Robotics for Sustainable Farming

By Sasha Zvenigorodsky

The movie I, Robot came out in 2004, telling the story of a society in which a population of highly intelligent robots that worked public service positions to keep people safe became part of a dangerous conspiracy to enslave the human race. This fantastical, futuristic robot theme is one that was quite popular throughout the early 2000’s. While watching movie star Will Smith conquer a dangerous robot regime on the big screen, it may have been difficult to imagine the ways in which robotics could be a realistic and helpful addition to society in the near future.

Today, robots regularly roam a plot of farmland in Urbana, Illinois. This plot of farmland is used by the Artificial Intelligence for Future Agricultural Resilience, Management, and Sustainability (AIFARMS) Institute. AIFARMS brings together researchers studying both artificial intelligence and agriculture. Core research areas at AIFARMS include computer vision, data science, machine learning and human-robot interactions. Their mission is to use these areas of research to address major challenges in agriculture, and fulfill important societal needs.

“Current agriculture production relies on unstainable labor needs, soil degeneration, herbicide/pesticide resistance, nitrogen runoff, greenhouse gas emissions, and animal welfare concerns,” says Jessica Wedow, AIFARMS executive director. “These critical challenges are difficult to tackle with human capacity and conventional technologies alone.”

Currently, AIFARMS is working on four different research projects. One of these projects involves the design and development of an AI-driven farm. The purpose of this project would be to alleviate the agricultural labor crisis and encourage sustainable crop management practices using teams of small, intelligent robots called agbots.

The US agriculture industry has faced widespread farmworker shortage over the years, due to dwindling rural populations and declining interest in agricultural employment. Farmers have been forced to find innovative ways to adapt, such as the implementation of agricultural technology. With the AIFARMS agbots, tedious agricultural duties like harvesting and scouting fields no longer need to be performed by farmworkers and can be fulfilled by the robots instead.

Sustainable crop management practices are also a major plus of the AIFARMS research projects. With a growing population and limited land and water, increasing the efficiency of the farming industry has been a very important societal goal. By using AI-driven farming techniques, the need for unsustainable standard farming practices decreases. For example, farmers can use agbots to weed plants beneath the crop canopy, instead of applying herbicides that are harmful to the environment.

In addition to different research projects, AIFARMS hosts a variety of education and outreach programs. These programs contribute to meaningful efforts to inspire the younger generation to explore digital agriculture and grow a skilled workforce.

As the agricultural community faces new challenges due to a fluctuating climate and growing global population, research within digital agriculture is becoming an increasingly important part of the solution.

Get Involved

Interested in learning more about this work? The AIFARMS annual conference will be held on September 7, 2023, in Urbana, Illinois, at the National Center for Supercomputing Applications (NCSA).

Additionally, the Center for Digital Agriculture at the University of Illinois at Urbana-Champaign, Center for Research on Programmable Plant Systems (CROPPS), and PhenoRob are organizing a full-day “Workshop on Agricultural Robotics for a Sustainable Future” at the IEEE/RSJ International Conference on Intelligent Robotics and Systems (IROS) 2023. This workshop will take place on October 1, 2023, from 9:00 a.m.–5:00 p.m. ET, in Detroit, Michigan. Researchers working in different areas of Agricultural Robotics and Precision Agriculture are invited to submit their work as abstracts to be considered for poster presentations and lightning talks.

Contact the Midwest Big Data Innovation Hub if you’re aware of other agriculture- or food-related people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Student Profile: Addison Graham

By Aisha Tepede

The Midwest Big Data Innovation Hub (MBDH) is committed to being a venue for outreach and engagement that increases the potential for benefitting society through the Priority Areas the organization leads and the amplification of other investments and opportunities.

One avenue for this is the National Science Foundation’s (NSF) recent Convergence Accelerator program track focused on disability-related research, which allows universities and nonacademic institutions to develop solutions to address societal challenges for persons with disabilities through convergence research and innovation within a collaborative and multidisciplinary effort. Our recent story on these awards explores them in more detail.

In this post, we will focus on a discussion surrounding the impact these projects have on people with disabilities with Addison Graham, a fourth-year undergraduate student at Illinois State University (ISU) studying Special Education—Specialist in Low Vision and Blindness, with a Certificate in Early Intervention and the president of ISU’s Braille Birds student group.

How did you decide on special education as a career and choose to emphasize low vision and blindness?
“I got here by how I believe most people get into the field, pure chance. I wanted to pursue a specialization of Special Education. When visiting Illinois State University’s (ISU) Summer Seminar, I was introduced to the three subfields of the major (i.e., LBS—Learning Behavioral Specialty, DHH—Deaf & Hard of Hearing, and LVB—Low Vision & Blindness). I chose to attend the LVB talk where an LVB professor talked to us about the field. My father then suggested I go into the field and see if I liked it; not wanting to do everything my father suggested but understanding that it was a great suggestion, I decided to go along with it. Now, I am a 4th year still majoring in Special Education with a Specialty in Low Vision and Blindness with a Certificate in Early Intervention (SED w/ LVB Cert. in EI).”

When working with individuals with disabilities, do you think it teaches you more about yourself and the type of educator you want to be?
“Absolutely! Training to become a teacher is a stressful, but rewarding, endeavor. Much reflection and analysis of what, how, and why you do the things you do in your lesson plans is thoughtfully considered at every step.”

With braille being one of the biggest inventions for visually impaired people, and as the world moves into more technological advances, what do you think is important for inventors to remember when creating new technologies to help the community?
“To answer the question, web developers must adhere to the Web Content Accessibility Guidelines (WCAG) Standards; however, *no new technologies are needed to support individuals with visual impairments. I have an asterisk there for a reason, which I will touch on in a moment, but let me explain my position.

The Asterisk: New technologies have changed the way Blind People live for the better. Some of these solutions were designed explicitly for the Blind Community, and others not so much, but what is important is how helpful they are to the people who use them on a daily basis.”

He adds, “It is important for inventors to consider and incorporate the Blind Community. This does not mean having one blind man look over the project and say, ‘Good enough, I think.’ But reach out to experts in the field of Education & Policy for the Blind. People who are blind will be your boss, employee, and consumer; why make something they can’t even use? Having organizations such as American Printing House for the Blind (APH), American Foundation of the Blind (AFB), Industries for the Blind and Visually Impaired (IBVI), and/or National Federation of the Blind (NFB) to consult with your company or team or having a separate person on the team dedicated to understanding and implementing accessibility into your specific project is a necessity.”

He closes with, “Remember, oftentimes this community doesn’t need a complete workaround, just a ‘digital ramp’ to allow them to access the same information as everyone else. If the Bus 101 Company creates an app to let people know when and where the bus routes are, it cannot be just a picture. If it is, then it should be accompanied by Alt Text that is easy for the blind user to navigate to find their stop just as easily as any sighted person. Accessibility to software, hardware, places, and products, is the gateway to independence, but if we only address the needs of these very real human beings whenever it is convenient for us, then we deprive real people of the opportunity to live their life on their terms.”

What is a “Digital Ramp”?
“The phrase ‘Digital Ramp’ refers to the common example people think of when they hear the word ‘accessibility,’ that is a physical ramp to a door for someone who is in a wheelchair. If a ramp refers to someone with a physical disability getting access to a building through the ramp rather than the inaccessible stairs, then the lack of a digital ramp can be thought of as a barrier for people who use technology but are unable to access it. Examples include the following: a deaf person not having the options for captions; an elderly person, someone who is technologically illiterate, or someone with a cognitive delay being expected to navigate a frustratingly unintuitive website to secure something necessary (e.g., government-subsided healthcare); or a blind individual using Bus 101’s app being shown a picture of the bus routes with no Alt Text rather than a description of when and where the buses will be.”

As the interview continued, Addison shared recommendations for industries in order for them to better support the Blind Individuals already using their services or inside of the field itself. See the table below:

Property Management Personnel or City PlannersUse of braille signs from reputable companies on everything permanent that has visual information (i.e., print text, pictures, models).

Use of tactual information on maps in parks, cities, airports, hospitals, shopping malls, etc.

Following American Disability Act (ADA) guidelines when designing buildings, indoor and outdoor spaces.

Consider designs that include and prioritize humans rather than cars.
Business & Education PersonnelUse digital document accessibility features to improve usability for individuals with visual impairments, such as:

      • If you have to, only use PDFs with text selectable or Object Character Recognition (OCR) and avoid using poor scan-in PDFs.
      • Use Headers (e.g., Title, Header 1, Header 2, etc.) and Repeating Header Row in Tables (i.e., using the “Repeat as Header Row at the Top of Each Page” feature in Table Properties under section “Row” allows Screen Readers and visual users to access the Header Row Title of the specific column they are in).
      • Use audio descriptions to describe what’s happening when the audio of the video does not tell you enough information (e.g., a step-by-step tutorial with light piano music playing in the background).
Hardware DevelopersUse of physical buttons and tactual indicators for all ports and cable types as well as access to screen-reading technology via software by using an AUX port.
Software DevelopersAdherence to the Web Content Accessibility Guidelines (WCAG) Standards as well as universally accessible screen-reading technology that is available via the hardware of an AUX port.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Cultivating Change: Finding Answers with Sustainable Urban Farming

By Sasha Zvenigorodsky

2019 USDA Food Access Research Atlas, showing the frequency of food deserts throughout the Midwest. The atlas indicates areas where a significant number of residents live more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket.
USDA Food Access Research Atlas, 2019
Low-income census tracts where a significant number or share of residents is more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket.

Most individuals native to Illinois would be shocked to hear that thousands of its residents reside in areas that are considered to be deserts. Not literal deserts, but rather food deserts, urban areas in which it is difficult to buy good-quality or affordable food. Although food deserts aren’t covered by dry sand and hot sun, both types of “deserts” have one glaring similarity: hostile living conditions due to lack of food resources. The 2019 USDA Food Access Research Atlas (at right) demonstrates the frequency of food deserts throughout the Midwest, indicating areas where a significant number of residents live more than 1 mile (urban) or 10 miles (rural) from the nearest supermarket. As food accessibility issues are exacerbated by climate change, these food deserts have the potential to grow even more expansive.

The Midwest Climate Summit concluded in late February, a three-day event hosted by the Midwest Climate Collaborative (MCC; led from Washington University in St. Louis), with the purpose of gathering climate leaders, researchers, and other interested parties to address the escalating issue of climate change and promote new partnerships and collaborations. The Summit hosted multiple speakers and workshops, with topics ranging from agroforestry and silviculture to designing a circular economy.

All these topics have the same main goal: addressing climate change. Here, we explore one session that highlighted the critical impacts of climate change on food accessibility within Illinois. As global warming brings on intense weather fluctuations throughout the United States, standard agricultural practices are jeopardized and traditional farmers are thrown into uncertainty. Without solutions to this issue, food deserts throughout urban areas are likely to expand.

Hosting a panel that included a small regenerative farm, a family orchard, and a beekeeper, the Midwest Climate Summit introduced just that: solutions—specifically, the concept of urban farming.

Urban farming entails both the cultivation and distribution of agricultural products within urban and suburban areas. Hydroponic/aquaponic facilities, community gardens, and rooftop farms are all examples of urban farming. These methods have excellent potential to provide healthy, fresh foods to underserved areas with limited nutritional access. They also address climate change in big ways. For example, various urban-farming methods can utilize less water, less light, and less soil than traditional farming can, proving to be more sustainable and climate-friendly.

The ability to educate and raise awareness on issues like climate change and food insecurity is a big reason why panels like the Midwest Climate Summit are so important. Nonetheless, they are often missing an important target audience: children. Promoting the importance of local urban food systems to school-age children can be the key to establishing more sustainable and environmentally friendly communities over time.

This is demonstrated perfectly by the Gardeneers organization of AmeriCorps. AmeriCorps is an independent agency of the United States government that engages Americans in service positions through stipended volunteer work organizations. One such organization, called Gardeneers, involves urban-farming education targeted towards underprivileged children living in urban food deserts within Chicago. Their mission is to help create a more equitable food system with the help of specialized school garden and farm programs within Chicago’s South and Westside schools. These programs can equip kids with the proper knowledge and skills to positively contribute to the environment and their communities.

“Climate change leaves these kids facing an uncertain future,” says Galina Fesseler, Gardeneers volunteer. “Educating kids about food accessibility and urban farming is a great way to invest in their health and development.”

Food is just one dimension of the larger impact that climate has on a region. Other sessions at the Midwest Climate Summit addressed related topics, such as water and health, which affect people in communities, and shared a wealth of information and resources that communities can use to help with climate resilience.

In collaboration with the MBDH, the MCC developed a prototype Climate Asset Map (CAM), which is an online interface that will help groups from different disciplines and sectors to access and contribute to climate-action information throughout the Midwest, such as information surrounding urban farming. The MCC received feedback from across the Midwest to a survey about information needs that researchers, practitioners, government agencies, and community groups have around climate-related resources. This informed the development of the CAM prototype, which was presented at the Summit for attendees to explore. The model was then refined and has just launched as the Midwest Climate Resource Network (CRN).

Urban farming is just one small example of the many ways to address climate change, hence the need for the CRN. With the help of this resource, organizations like Gardeneers can be interconnected with other groups throughout the Midwest, allowing for collaboration and collective success within the various realms of climate work.

Get Involved

Contact the MBDH if you’re aware of other agriculture- or food-related people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

New NSF Convergence Accelerator Midwest disability-related awards

By Aisha Tepede

The National Science Foundation (NSF) has taken a new approach to build upon basic research and discovery to accelerate solutions toward societal impact by providing award funds to academic institutions across the USA with the opportunity to develop research projects.

Individuals who have disabilities deal with hindrances restricting them from achieving better economic opportunities, quality of life, health, and wellness. The NSF’s Convergence Accelerator program enables universities and nonacademic institutions to develop solutions to address societal challenges through convergence research and innovation within a collaborative and multidisciplinary effort. Recently, the program made 16 awards under its Track H: “Enhancing Opportunities for Persons with Disabilities,” including 6 in the Midwest. The transdisciplinary program builds upon basic research to develop new technologies and accelerate novel solutions that can address challenges faced by persons with disabilities.

One arena of the opportunities includes accessibility for those who are visually impaired.

Saint Louis University, in partnership with nonprofit and industry collaborators, received funding for a program that focuses on those with blindness or visual impairments (BVI). The program aims to address the disparities seen among the BVI population. With many members being disproportionately unemployed, unable to travel independently, and limited in furthering their education, this program aims to bridge the gap and create inclusive approaches to information access and strengthening inclusion among those with disabilities.

Another team focusing on visual impairment is led by Wichita State University, with collaborators at Kansas State University and Georgia Tech. In order to address national health and welfare, the team is fostering the formation of MABLE (Mapping for Accessibility in BuiLt Environments). The design is meant to allow those with visual and mobile impairments to navigate spaces through digital accessibility maps of indoor environments. Innovations such as these create vital opportunities for people with disabilities to foster daily practices of independence and develop new frameworks for quantifying economic benefits.

Other researchers in the Midwest are doing related work on visual accessibility. Professor JooYoung Seo serves as the Director of the Accessible Computing Lab in the School of Information Sciences at the University of Illinois at Urbana-Champaign (UIUC). “One of the ongoing projects in our lab is the development of an accessible data visualization system, particularly designed for blind and low-vision users,” Seo said. “This system leverages multimodalities like sound, speech, and braille to allow users to explore and analyze data. This project is of paramount importance, particularly in today’s digital era where data literacy is a crucial skill for everyone. By creating an accessible data visualization system, we are providing equitable access to visual information and contributing to data literacy for all individuals, regardless of their dis/abilities. This project illustrates our commitment to designing technology that is inclusive and supportive of everyone’s data needs.”

Seo also serves as senior personnel on the Delta high-performance computing (HPC) project, funded by NSF and led from the National Center for Supercomputing Applications at UIUC. Seo’s role involves identifying and addressing accessibility issues. “Our goal is to improve the interface to make it more inclusive for users with disabilities. The essence of this project lies in its potential to transform accessibility in the realm of high-performance computing. In a field where high efficiency and speed are paramount, we must also remember that true innovation should be accessible to all. Delta strives to break down barriers and create an environment that is equally beneficial and inclusive for all users, regardless of their abilities. This project underscores the principle that every user, regardless of their abilities, should be able to utilize technology with ease.”

The impact these projects have on people with disabilities is invaluable as well as for those who work in the field or plan to. Addison Graham is a fourth-year undergraduate student at Illinois State University (ISU) studying Special Education—Specialist in Low Vision and Blindness, with a Certificate in Early Intervention (SED w/ LVB Cert. in EI) and the president of ISU’s Braille Birds. The group is a registered student organization (RSO) that fosters education and spreads awareness about the blind and visually impaired community.

As an incoming educator in Special Education, Addison states,

            “With innovations like MABLE filling the need for greater ease-of-use navigational accessibility indoor of buildings, individuals with and without visual impairments could greatly benefit from the mandated reporting of a building’s interior design.”

Other teams receiving NSF awards under the Convergence Accelerator program include Michigan State University, Purdue University, and Northwestern University, which focus on projects for individuals who have speech impediments or are hearing impaired and create mobility independence for individuals with motor impairments. Projects such as these open opportunities to increase wellness and navigational accessibility for persons with disabilities.

To see a more in-depth description of each research project being conducted at various universities across the USA, see the table below.

Although the awardees each have different approaches and scopes of involvement of opportunities for persons with disabilities, there is a shared interest in synergizing work through facilitated collaboration in order to cultivate improved situations of development for marginalized populations. The Midwest Big Data Innovation Hub (MDBH) provides a venue for outreach and engagement that increases the potential for benefitting society and the themes seen with the institution’s awards. Collaborations with MDBH foster the use of data in developing solutions to enhance the quality of life and employment opportunities for persons with disabilities. These and other activities address topics that bring together diverse perspectives that open solutions for persons with disabilities.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Summary of new NSF Convergence Accelerator Midwest disability-related awards

Bridging the Fragmentation of Information Access – An Integrated, Multimodal System for Inclusive Content Creation, Conversion, and Delivery (Saint Louis University)This project aims to address information access as a consolidated initiative to create a unified framework for authoring accessible materials.
Convergent, Human-Centered Design for Making Voice-Activated AI Accessible and Fair to People Who Stutter (Michigan State University)This project aims to resolve limitations in voice technology by developing and implementing policy, advocacy, and AI-based solutions to make voice technology accessible and fair to people who stutter.
Developing Experiential Accessible Framework for Partnerships and Opportunities in Data Science (for the deaf community) (Purdue University)This project aims to create strategic initiatives to overcome barriers and biases that deaf individuals face in the workplace for deaf learners in order to teach data science content.
Leveraging Human-Centered AI Microtransit to Ameliorate Spatiotemporal Mismatch between Housing and Employment for Persons with Disabilities (Wayne State University)This project aims to promote disability inclusion in workplaces by enhancing the availability and reliability of paratransit services by delivering an open-source human-centered Artificial Intelligence (AI) technology that aids microtransit services.
Mobility Independence through Accelerated Wheelchair Intelligence (Northwestern University)This project aims to accelerate the accessibility and utility of power wheelchairs by leveraging practical machine intelligence to enhance safety and facilitate independent wheelchair operation.
Towards a Community-Driven Framework for the Creation and Impact Analysis of Digital Accessibility Maps with Persons with Disabilities (Wichita State University)This project aims to use MABLE (Mapping for Accessibility in BuiLt Environments) to provide digital accessibility maps of indoor environments with an interface for assessing, planning, and navigating, based on the affordances and capabilities of the user.

Overcoming Cybersecurity and Interoperability Challenges in the Water Sector

By Iishi Patel

Cybersecurity threats to drinking water and wastewater systems have been a growing concern in recent years. The increasing use of automation and technology integration in these systems has made them more vulnerable to cyber attacks, potentially putting public health and safety at risk. There are more than 52,000 community water systems in the United States, and most are run by local governments, many of which are very small and may not have the resources to improve their cybersecurity.

In February 2021, a hacker gained unauthorized access to a water treatment plant’s computer system in Oldsmar, Florida. The hacker raised the level of sodium hydroxide in the water supply, which could have caused serious health problems if not detected and reversed quickly. Since then, many states have issued alerts to water systems and taken steps to improve their cybersecurity measures. However, small water utilities often lack the resources to ensure their cybersecurity is strong, and there are concerns that insiders could also pose a threat.

The Water Data Forum’s latest episode, held on March 9, 2023, focused on cybersecurity and interoperability challenges faced in the water sector due to the adoption of digital capabilities, with an emphasis on developing national databases for water pipes, implementing AI, and minimizing cybersecurity risks. In the panel discussion on intelligent water systems, experts from various fields came together to share their insights and experiences. The focus was on the challenge of creating a national database for water pipes, which requires collecting data from various utilities in different formats and using different software. The speakers emphasized the need for data to be standardized, interoperable, and accurate to enhance service delivery and ensure that data analysis provides useful knowledge and wisdom. Dr. Sunil Sinha, the Director of the Sustainable Water Infrastructure Management (SWIM) Center at Virginia Tech, proposed that the water sector in the USA can learn from other advanced sectors such as transportation and smart electric grids to speed up their adoption of data-related standards and interoperability models to ensure swift adaptation of cybersecurity practices.

Additionally, in November 2022, the National Cybersecurity Center of Excellence (NCCOE) announced the formation of a group dedicated to securing the water industry from cyber threats. The NCCOE seeks guidance from the industry and has created cybersecurity best practices for the water sector. The organization’s goal is to offer education, testing, and complementary resources to support the water industry in developing stronger defenses against cyber attackers.

The Biden-Harris Administration has extended the Industrial Control Systems (ICS) Cybersecurity Initiative to the water sector, with the Water Sector Action Plan outlining actions to improve cybersecurity over the next 100 days. The plan will assist owners and operators in deploying technology that provides cyber threat visibility and sharing cybersecurity information with the government and stakeholders. The plan will initially focus on utilities serving the larger populations but will lay the foundation for enhanced ICS cybersecurity across water systems of all sizes.

Overall, when it comes to designing a cybersecurity strategy for the water sector, it is important to assess the organization’s current ability to manage people, processes, and technology, and determine their level of maturity. After this understanding, we need to secure the organization’s data with a focus on asset management, data integrity, remote access, and network segmentation and aim to align business needs and cybersecurity requirements. Hence, interoperability and cybersecurity should be viewed as complementary rather than separate, with increased interoperability potentially leading to improved cybersecurity. However, to implement these kinds of strategies on a national level, there is a need for a common methodology and standards for the water sector, which can be achieved through standardized system engineering. It is suggested that academic institutions and professional associations collaborate to lead the development of these standards.

Get Involved

Join the upcoming Water Data Forum webinar on June 16, 2023, which will be focused on a cross-sector discussion of wastewater surveillance for public health.

Contact the MBDH to learn more, or if you’re aware of other people or projects involved in water data and cybersecurity that we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Workshop on Data for Good for Education for Faculty Opens for Registration

By Aisha Tepede

The continued growth of the Data for Social Good (DSG) movement provides an opportunity to increase student motivation and persistence within courses and degrees in data science. To help accelerate faculty use of data for good projects in courses, the Midwest Big Data Innovation Hub (MBDH) is hosting a free workshop in partnership with Trinity Christian College on June 2–3 near Chicago. Some travel support is available, including for early-career faculty and those from primarily undergraduate institutions (PUIs) and minority-serving institutions (MSIs).

The Workshop on Data for Good for Education (D4G4ED) aims to provide professional development opportunities for instructors seeking to engage their students through meaningful social good projects within a classroom setting and to learn about the latest developments in this field.

The workshop is meant to inspire, educate, and most importantly, allow faculty to share and prepare materials for use within their teaching context. The workshop will support faculty in developing their teaching to better incorporate the DSG movement, which provides a natural connection to relevance with grassroots-level improvements in our society while promoting the broad applicability of data science. This important component of increasing persistence and success for our current generation of students is connecting their coursework to meaningful change or outcomes.

The workshop aims to create networking opportunities for students, faculty, schools, and social good organizations, relating to nonprofits and governments with data science and analytics needs. This event facilitates a venue for sharing successes from projects and courses that use DSG while acting as an onboarding and support platform for faculty and schools interested in including DSG within their schools.

The two-day workshop will consist of facilitated sessions to highlight existing teaching practices around data for good, including Plenary Talks, structured workshop sessions, a “Marketplace of Ideas and Innovations,” group working time, and a networking session.

Guest speakers at the workshop include Dr. Dharma Dailey from the eScience Institute at the University of Washington and Dr. Richard Blumenthal from the Computer and Cyber Sciences Department at Regis University. Each speaker has a unique background surrounding data-intensive research and Artificial Intelligence (AI) research. Drs. Dailey and Blumenthal will be leading workshop sessions on embedding DSG activities in course curricula, and how to engage with external clients to develop real-world projects that are appropriately scoped for student work. The speakers and the workshop session aim to increase knowledge and interest in research, social good, and curricular-innovation goals.

This workshop is supported in part by the National Science Foundation through the MBDH Community Development and Engagement (CDE) Program, through a proposal developed by Karl Schmitt, Data Analytics Program Coordinator and Assistant Professor of Data Analytics at Trinity Christian College.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or data science education projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Diving into Data: Tackling Aquatic Invasive Species with the Help of Illinois RiverWatch

By Sasha Zvenigorodsky

View of the Pecatonica River from Van Buren Street Bridge in Freeport, Illinois. Photo by Andra C. Taylor, Jr.
Photo by Andra C. Taylor, Jr./Unsplash

Aquatic invasive species (AIS) are freshwater or marine organisms that have been introduced beyond their native range. The word “invasive” speaks volumes, given the current state of aquatic ecosystems all around the world. Over the past 100 years, invasive species have contributed extensively to global aquatic biodiversity loss. Their presence has the potential to destroy entire ecological communities and threatens the safety of native species.

In the Upper Mississippi River Basin (UMRB), the threat of AIS is even more imminent due to its interconnected stream network and proximity to the Great Lakes. Species like silver carp, zebra mussels, and water hyacinth have all made the UMRB their home, growing fast and reproducing even faster. Left uncontrolled, these invasive species deplete important resources from the UMRB ecosystem that native species rely on for survival.

Thankfully, there are many organizations within the Midwest that work specifically towards keeping this issue controlled, one such organization being the Illinois RiverWatch Network. Established in 1995, the Illinois RiverWatch Network provides volunteers with an opportunity to monitor stream habitat and water quality within Illinois waterways. These volunteers, better known as “citizen scientists,” collect important data that is used to determine how Illinois stream conditions are changing over time. For example, citizen scientists participate in an annual biological survey where they collect data on the diversity of macroinvertebrates living within a stream. According to the RiverWatch Network, a healthy aquatic ecosystem is indicated by the presence of macroinvertebrates, which are more sensitive to changes in water quality.

The volunteer-based science that RiverWatch promotes is significant for a number of reasons. “As researchers, we can only visit so many sites in a year. We just don’t have the time, the resources, the budget for travel to hit everywhere,” says Dr. Danelle Haake, Illinois RiverWatch director. “The people who are living in that community are going to be the ones who notice if something starts to change if something goes wrong. They’re the ones that can bring it to the attention of other stakeholders, and of people who can make changes in their community.” Having local volunteers to monitor Illinois stream conditions allows for more data collection within more communities statewide.

The Illinois RiverWatch Network is just one example of an organization that gathers data on AIS movement in the Midwest. There are many groups, including academic institutions and government agencies, which do the same. Despite this, there is no comprehensive, accessible inventory of all this data. This indicates a major barrier to addressing the AIS issue. Important data, such as the annual biological survey of the Illinois RiverWatch Network, falls short of its true potential when there is no opportunity for this information to be integrated into other disciplines that also focus on AIS management.

This year, the Midwest Big Data Innovation Hub’s Water Quality priority area team will be organizing a workshop and other activities to address this issue directly, bringing together individuals from different backgrounds to focus on challenges regarding AIS data collection and interoperability. Prior to the workshop, the Water Quality team will be sending out a community interest survey to gain a better understanding of key data challenges and community needs surrounding AIS.

“The unique and vital roles of the Great Lakes and Mississippi River to the Midwest face challenges from aquatic invasive species,” said John MacMullen, MBDH executive director. “Through our work understanding the data needs of the diverse stakeholders addressing AIS challenges in the region, we hope to facilitate new collaborations that can mitigate impacts to human health, foodsheds, biodiversity, and agriculture.”

The spread of AIS spans multiple different areas, including biological, hydrological, and ecological topics. Related data is collected separately with tools unique to each domain. By integrating and improving data access, AIS research can be accelerated and AIS management can be drastically improved.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

New Opportunities for student data science enthusiasts: NSDC launches chapter in the Midwest

By Iishi Patel

Data science awareness is becoming increasingly important in today’s world as the amount of data generated daily is growing exponentially. With the right skills and knowledge, data science can be leveraged to solve complex problems across various domains, from healthcare to finance and beyond. Therefore, the need for initiatives like the National Student Data Corps, which aims to create awareness about data science, has never been more critical.

MBDH Student Community Monthly Webinar and Slack Community tile showing three students with their laptops sitting together at a table.

The National Student Data Corps (NSDC) is a community-based project that teaches data science fundamentals to students across the USA and other countries, with a focus on underserved students and institutions. It began in 2020 with the launch of its first chapter in the northeastern region. Today, the NSDC community includes over 3,550 individuals from 532 institutions in the USA and 26 other countries. The NSDC’s goals include giving access to resources and research opportunities in data science. It also provides resources for career development in this field and shows its commitment to diversity, equity, inclusion, and accessibility through panel discussions, Slack discussions, and newsletters.

With the growth of data science enthusiasts in the Midwest, NSDC proudly launches its Midwest Regional Chapter under the leadership of Florence Hudson, the executive director of the Northeast Big Data Innovation Hub; Emily Rothenberg, the program coordinator; and Lauren Close, the operations manager. The NSDC’s Midwest Regional Chapter plays a crucial role in expanding access to data science education and resources to students and enthusiasts across the region. By providing a platform to learn, share ideas, and collaborate, the chapter empowers its members to develop their data science skills and advance their careers. The Midwest Regional Chapter is also supported by J.D. Graham and John MacMullen from the Midwest Big Data Innovation Hub. The chapter already has members from Illinois, Michigan, and Minnesota and encourages students, enthusiasts, and learners across the region to grow and learn about data science in new and exciting ways.

The Midwest Regional Chapter aims to reach out to a broad audience, from students who want to learn data science outside of a regular institution to enthusiasts at all levels. The program coordinator Emily describes the Midwest Regional Chapter as a space to continue their learning and a sense of community for people who cannot currently go to school, or a higher education institution, and want to keep up with data science technologies. The chapter is in the process of planning events like data science mentorship opportunities, webinars, and career panels.

The chapter is ready to invite participants for their flagship event, the 2023 Data Science Symposium, hosted by NSDC. Here, participants will get to present their research findings on a data science topic of their choice. The winner gets to showcase their research at a live event sponsored by NSDC.

In the immediate future of the chapter, the leadership aims to build a one-stop repository of resources for data science enthusiasts and invite students from all over the Midwest to join. The leadership also looks forward to having student representatives in various universities and colleges throughout the Midwest. The chapter also actively maintains a Slack channel to keep members updated about their latest events and engage in mentorship.

To become a part of the Midwest Chapter, you can sign up here. You can also follow their events calendar to stay up to date. A forthcoming event in collaboration with the Midwest Big Data Innovation Hub is an information session about Exploring Science Policy Careers. It’s a great opportunity to learn about and interact with the chapter on April 7, 2023, at 12:00–1:00 p.m. CT/1:00–2:00 p.m. ET.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other data science education-related people or projects we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

New NSF Awards to Accelerate Food and Nutrition Security

By Aisha Tepede

Since 1951, the National Science Foundation (NSF) has been awarding academic institutions across the U.S. the opportunity to develop research projects. More recently, the Foundation has taken a new approach to build upon basic research and discovery to accelerate solutions toward societal impact.

The NSF’s Convergence Accelerator program enables universities and nonacademic institutions to develop solutions to address societal challenges through convergence research and innovation within a collaborative and multidisciplinary effort. This takes the form of themed “tracks,” focused on particular challenges, which are defined through a community-input process. A recent track on Food and Nutrition Security led to several awards for projects involving data use in sustainable agriculture, specifically around food supply chains to build resilience to climate change and natural hazards, using digital tools for agriculture and food, and seeing how food security, equity, health, and environmental justice innovations positively impact local communities.

With the lack of consistent access to enough food for individuals living in a household growing each year, several universities have chosen to create innovative and tangible solutions to minimize the burden it holds on many members of society. Throughout the USA, socially disadvantaged neighborhoods struggle with finding sustainable solutions for food and nutrition security. Some reasons include that lack of access to food varies greatly between communities and that there are climate issues such as communities that are at risk for hurricanes and other natural disasters. Universities such as the University of Arkansas at Pine Bluff and University of Maryland, Baltimore County are creating solutions to reduce disaster-induced food and nutrition insecurity and improve health outcomes among underserved and minority communities.

The push for decreasing food insecurity has opened an arena for new and innovative digitals to be created. Institutes such as George Mason University and the University of Houston are focusing on and creating progressive data-driven systems that assist in crop management to increase US agricultural production as well as health issues that plague disadvantaged communities by building locally oriented food-charity ecosystems that incorporate culturally aware food distribution to community members. Virginia Tech Applied Research Corporation also seeks to increase vegetable production capacity by developing climate-smart technology sustainable for precision agricultural practices that allow for effective and adaptive decision-making.

Along with food insecurity plaguing many communities, issues surrounding environmental justice and climate change have risen over time. Schools such as the University of California–Santa Barbara and Pratt Institute have projects that predict the ability to collaborate with stakeholders along the food system to develop actionable models tailored to their needs and decision-point and development projects that benefit agriculture and soil health on land. These projects aim to understand and anticipate the vulnerability of the global food system to predictable climate shocks.

To see a more in-depth description of each research project being held at various universities across the USA, see the table below.

Although the awardees each have different approaches and scopes of community improvement, there is a shared interest in synergizing work through facilitated collaboration to cultivate improved situations of development for underrepresented and underserved rural populations. The Midwest Big Data Innovation Hub (MDBH) provides a venue for outreach and engagement that increases the potential for benefitting society and the themes seen with the institution’s awards. Collaborations with MDBH foster the use of data in sustainable agriculture, including around food supply chains to build resilience to climate change and natural hazards. One example is the “Enabling a Smart and Equitable Agriculture Ecosystem” working group that the MBDH co-leads. These and other activities address impacts on local communities, including food security, equity, health, and environmental justice.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other agriculture- or food-related people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

NSF Convergence Accelerator Track J Awards for Food and Nutrition Security

Aqua Sacs for Sustainable Agriculture in a Changing Climate (Pratt Institute)This project aims to understand and develop the industrialization steps required to produce Aqua Sac at a commercial scale.
Artificial-Intelligence-Based Decision Support for Equitable Food and Nutrition Security in the Houston Area (University of Houston)This project brings together civic collaborators with university researchers to develop and build a locally oriented food-charity ecosystem based on data-driven smart technologies in the Greater Houston region.
Building a digital twin for national-scale field-level crop monitoring, prediction, and decision support (George Mason University)This project aims to ensure food and nutrition security by enhancing crop productivity and reducing environmental footprint in the USA through wide adoption of the data-driven approach enabled by CSDT, which is a CropSmart Digital Twin that accurately represents the current conditions and predicts future-crop cropping systems.
Convergence Towards a Disaster Resilient Food System (University of Maryland Baltimore County)This project aims to create a Food Index for Resilience, Security, & Tangible Solutions (FIRST) that measures food system functioning. The FIRST will provide a tool for communities preparing for, responding to, and recovering from disasters and environmental change.
Data-driven Agriculture to Bridge Small Farms to Regional Food Supply Chains (University of Arkansas)This project advances the health and prosperity of the United States’ population, as well as environmental stewardship, through its focus on food and nutrition security.
Food EducatioN for Nutritional security and Empowerment in Local communities (FENNEL) (University of Arkansas at Pine Bluff)The project involves a robust set of activities to engage local communities in addressing nutritional insecurity through an educational and outreach-tailored approach to address community needs.
Food, Land, Water Environmental Open-Source Risk Intelligence Synthesis Model (FLOWER-ISM) (Mesur.io)The project aims to involve technological advances and assistance to areas of focus surrounding identifying risks for conflict, water shortage, and food availability to ensure access to food is met for all citizens.
MidAtlantic Food Resiliency Network: Securing the Future of Food through a Multi-Mindset Approach (University of Maryland, College Park)This project focuses on the use of surveys, focus groups, a digital tool kit, and technology to address the complex and interconnected challenges of nutritional and food security.
Network Of User-engaged Researchers building Interdisciplinary Scientific infrastructures for Healthy food (NOURISH) (University of California–San Francisco)This project aims to solve the problem of food swamps by equipping responsible business entrepreneurs situated within these communities with data and information for developing and marketing healthy, sustainable foods.
Precision Agriculture for a Resilient Vegetable Supply Amidst Climate Change (Precision Ag4Veggie) (Virginia Tech Applied Research Corporation)This project aims to increase vegetable production capacity throughout the USA by developing climate-smart, technologically and economically efficient, and environmentally sustainable precision-agricultural practices that enable more effective and adaptive decision-making.
Predicting the effect of climate extremes on the food system to improve resilience of global and local food security (University of California–Santa Barbara)This project aims to help identify drivers of hunger that are relevant in different settings within developing and developed countries in hopes of facilitating the development of protocols for decision-maker coproduction of models.
Rapid detection technologies and decision-support systems to mitigate food supply chain threats (University of Missouri–Columbia)This project aims to provide research and training opportunities for students to learn about the convergence-science approaches at the intersection of food science, public health, animal sciences, data science, and sensing technology as well as integrating multiple innovative features of an impedance-based biosensor.

New working group focused on interoperability of agricultural data

By Sasha Zvenigorodsky

In the face of increasingly challenging climate issues and an ever-growing population, digitization has played a large role in agriculture improvement throughout the years. Innovative technologies such as robotic systems, moisture and temperature sensors, and semiautonomous aviation systems have all revolutionized standard agriculture practices. Consequently, the increase in digital agriculture has led to an increase in various supply chain data needs and has also raised several questions about data interoperability. Organized and effective data exchange between agricultural information systems is crucial to allow the agriculture community to reap the benefits of digitalization.

A new digital agriculture interoperability working group believes that understanding agricultural supply chain data needs will benefit both farmers and large agribusiness corporations alike. The group, co-led by the Midwest Big Data Innovation Hub (MBDH) and the Illinois AgTech Accelerator, in partnership with the IEEE Standards Association, plans to identify interoperability issues caused by the flood of information produced by new agricultural technologies. The group’s goals include creating new proposals for data provider standards and certificates, as well as making recommendations for the best practices that will help increase collaboration surrounding agricultural data collection and management.

“The MBDH is happy to be co-leading this working group with our partners,” said John MacMullen, MBDH Executive Director. “The MBDH Digital Agriculture community has been a leader in exploring the challenges and opportunities of data in agriculture, particularly with sensors and autonomous vehicles. With this partnership, we are expanding the reach to cross-sector collaborators across the ag-food supply chain.”

On December 5, 2022, the group hosted a kickoff webinar on Integrative Smart Agriculture Data to address challenges within data protection and interoperability. The webinar was designed to facilitate productive conversations and idea sharing that can help lead to potential solutions to previously mentioned challenges.

Throughout the upcoming year, the group will continue to host various activities regarding digital agriculture. The next working group meeting will be February 7, 2023, at 10 a.m. CT (online).

The working group welcomes participants from academia, industry, and government agencies that are interested in smart agriculture. Visit the group’s web page to learn more. To join the group and attend meetings, an inquiry can be sent to IEEESmartAg-Info@ieee.org.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Building hands-on data science skills with the Midwest Carpentries Community

By Aisha Tepede

Science relies more and more on software and computing technologies, but researchers often don’t receive the training they need to effectively use these tools. A worldwide organization called The Carpentries is trying to help with hands-on training that is developed and taught by a community of volunteer experts.

Since 2012, the organization has run 3,799 workshops in 68 countries and trained 4,108 instructors. Moreover, they have had the ability to deliver 35 collaboratively developed, open lessons to 95,000 novice learners for at least 110 member sites. The organization has since been a pillar for a global and inclusive community in order to provide and teach coding and data skills. The Carpentries clusters its instructional content into three brands: Software Carpentry, Data Carpentry, and Library Carpentry.

To build the community at local and regional levels, The Carpentries are helping to facilitate subgroups in geographic areas. The Midwest Big Data Innovation Hub (MBDH) co-leads the Midwest Carpentries Community (MCC), which is open to all in the 12-state region, regardless of institutional affiliation.

The MCC began as a proposal from Dr. Sarah Stevens at the University of Wisconsin to the MBDH Community Development and Engagement (CDE) Program, which incubates new community initiatives.

Through monthly meetings and other activities, MBDH and the MCC members showcase The Carpentries instructors and best practices at academic institutions and other organizations, and provide a welcoming venue to develop collaborative efforts toward building regional capacity for The Carpentries instructors at smaller and underresourced institutions in 12 Midwest states.

The MCC strives to foster a community of practice to facilitate knowledge sharing and collaboration. It will be developing a centralized website to coordinate trainings and subject-matter workshops, and will be using mentoring programs to empower community members to act as hosts and instructors. The organization provides an interpersonal network through connections with other institutions, both domestically and internationally. Sarah Stevens stated,

“The project aims to build ‘hands-on data science instruction capacity,’ by using the existing curriculum and workshop model of The Carpentries, which includes communities of instructors, trainers, maintainers, helpers, and supporters who share a mission to teach foundational computational and data science skills to researchers.”

“Our partnership with Sarah and the University of Wisconsin has been very successful,” said John MacMullen, Executive Director of the MBDH. “In 2023, we plan to continue our monthly community calls as a part of The Carpentries new regional communities initiative. We will also open our Carpentries membership to underresourced institutions that want to train new instructors and establish new Carpentries activities.”

The MCC meets on the last Monday of each month. The Carpentries also has a Slack community that features a Midwest community channel for ongoing discussions and networking.

Get Involved

The MCC is supported by the National Science Foundation through the MBDH Community Development and Engagement (CDE) Program.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or data science education projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Meet the Artist: Ariann Rousu and the Native Dancer Project

By Isabel Alviar

Art is how a culture records its life, how it poses questions for the next generation, and how it will be remembered. A team from the AI and VR Lab at the University of North Dakota (UND) is developing a multiuser computer environment for competitive powwow dancing, called the Native Dancer Project, which uses art and technology to embody Native culture. Characters within the multiverse will move in ways associated with Native dancing and consist of models dressed in street clothing as well as in Native dance regalia found in dances custom to the Anishinaabe, Dakota, Lakota, Sioux, and other northern plains-associated tribes.

Different angles of Native dance regalia for a female digital character.



Ariann Rousu

Among the team of artists and designers is Ariann Rousu, whose work involves designing the digital gaming characters. Ariann has received a Photography and Digital Imaging certification, earned her Associates Degree in Liberal Arts and Fine Arts, and graduated from UND with a Bachelor of Fine Arts degree in 2022. In addition to her extensive art and design background, she brings a unique perspective to the Native Dancer Project from growing up on a reservation in Callaway and as a current member of the White Earth Ojibwe Nation in Minnesota. She says about the project, “It has always been important to me to keep learning and expanding my skill set as an artist as well as play my part in being prideful of, preserving, and sharing my Native culture. This project is challenging me to do just that, and I am grateful for the opportunity.”

NASA space suit

Interestingly, Ariann’s role on the Native Dancer Project did not actually start with designing. When she first started working in the AI Lab at UND, her job was to test the range of motion of a space suit for NASA potentially going to Mars and perform data analysis on the movements. In order to do so, her team tested multiple individuals in the space suit using motion picture software by putting sensors all over their bodies and recording numerous movements using small cameras. Her space suit research was a great learning opportunity for the motion picture capture process and developing her visual skills as an artist.

Since then, Ariann’s main focus has been creating the digital characters and their clothing for the Native Dancer Project. The goal of these characters is not to be modeled after a specific individual, but rather, they are being developed to represent someone who could be a member of a northern plains-associated tribe. A large part of Ariann’s work when designing these game characters is trying to maintain a level of realism and respect so they are not too cartoon-like and accurately portray modern powwow dancers today. She says, “Even though I am Native, it is important to remain aware of and be open to learning how to more accurately represent the culture and dances.” Additionally, her goal for creating the clothing is to keep it modern, stylish, and modest, while maintaining Native influence.

Male digital character for the Native Dancer Project.

Female digital character for the Native Dancer Project.

Photography is about light, and oftentimes, digital art does not look realistic because people do not understand how light works in the digital realm. For a project centered around realistically portraying Native culture, in the early stages of the project, it was less about creating characters and more about Ariann learning how to use new tools proficiently. From her previous photography experience, she had worked with the Adobe Creative Suite and other 3D modeling programs, but she was also introduced to new software for the Native Dancer Project. The characters for the project are being developed using a program called Character Creator 4 (CC4) by Reallusion, where designers can customize avatars in various styles. The clothing is being created with a program called Marvelous Designer that helps artists design garments and add intricate patterns and detailing for 3D characters. Every week, Ariann writes blog posts detailing the progress she has made, such as the steps she took, and any challenges that arose. At this stage, Ariann has successfully developed two characters—a male and female—with realistic features and characteristics. Additionally, she has completed a few street clothing outfits for the characters that include articles of clothing such as pants with basic patterns, fitted t-shirts, skirts, etc. Her goal for the next month is to have the first piece of regalia finished, a traditional Jingle Dress for the female character. Further down the line, her goal is to have more characters with multiple regalia features. She also hopes to use her motion picture capture experience to record real Native dancers, then use and modify the data to help create fully dressed characters that demonstrate powwow dancing.

Native dance regalia number 1 for a female digital character.

Native dance regalia number 2 for a female digital character.

If art is how a culture records its life, then the beauty of both art and culture is that they are ever-changing with time. Although Ariann has her goals for the direction of the Native Dancer Project, she admits, “Even I don’t know exactly what it’s going to look like in the future. But it will be interesting and I’m excited to see where it goes.”

Get involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in our activities, which include a Data Science Student Community and other regional activities, such as the Collaboration Cafe and the Midwest Carpentries Community.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Building a Climate Asset Map with the Midwest Climate Collaborative

By Sasha Zvenigorodsky

This story is part of a series on partnerships developed by the Midwest Big Data Innovation Hub with institutions across the Midwest through the Community Development and Engagement (CDE) Program.

Climate change—two words that have become increasingly popular throughout the scientific community as the world begins to see its destructive impacts across the globe. Though the rise in climate concerns for the future may appear to be a source of fear and uncertainty, many scholars, researchers, and academic organizations have regarded it as more of a call to action. This is where the Midwest Climate Collaborative (MCC) comes in.

Midwest Climate Collaborative Logo

The Midwest Climate Collaborative is headquartered at Washington University in St. Louis, Missouri, directed by Heather D. Navarro. This program is exclusive to a 12-state region in the Midwest and serves as a coordinating group for cross-sector responses to the ongoing climate crisis, with the objective of spreading knowledge about the issue as well as encouraging leadership and cross collaboration between various organizations to address the problem.

The MCC is a relatively new organization that was launched following the conclusion of a Think Tank series that was centered around outreach and engagement for climate action. By the end of the series, it was apparent that there is a plethora of great climate work being done across different institutions throughout the Midwest. Despite this, there are issues in their ability to connect and achieve collective success. Thus, participating Think Tank partners came together to craft strategies and objectives for the MCC, which was ultimately launched in January of 2022.

Throughout this past year, the MCC has established a variety of different strategic projects. One, launched in collaboration with the Midwest Big Data Innovation Hub (MBDH), is called the Climate Asset Map (CAM). This project has a goal of helping audiences such as researchers, practitioners, and community groups to easily access and contribute to climate action information that already exists in the region.

Currently, many governments and nongovernmental organizations (NGOs) local to the Midwest have limited resources to find and implement the latest climate research. The CAM serves to bridge this gap via an online, user-friendly interface. The assets of CAM could include data sets, research labs, training programs, and more. “Above all, I want this project to encourage people to invest in the Midwest,” says MCC Executive Director Heather Navarro.

As of now, the CAM group is moving forward in conducting a needs assessment survey with the help of a funded partnership with the MBDH. The needs assessment survey will help with the development of the CAM by determining which resources would be most beneficial for potential users to achieve success within their climate work. The survey results will be shared at the Midwest Climate Summit in February 2023, and will be distributed electronically over email and social media.

Although the fight against climate change is not an easy one, the MCC has worked as a catalyst to create a strong, interconnected Midwest region, which will certainly make it easier.

Get Involved

Contact the MBDH if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

MBDH Partners on New Data Science Workshop for Underrepresented High School Students

By Aisha Tepede

This story is part of a series on partnerships developed by the Midwest Big Data Innovation Hub with institutions across the Midwest through the Community Development and Engagement (CDE) Program.

Deciding what to do after high school can be overwhelming. There are various academic and career options that are provided but many students may feel uncertain and unprepared to make those big decisions. In central Michigan, high school students from several rural towns have the opportunity to learn about data science concepts for future careers at a summer workshop cosponsored by Central Michigan University and the Midwest Big Data Innovation Hub (MBDH).

Central Michigan University (CMU) holds inclusivity as core to its mission. According to the CMU mission, vision and values site, the institution prides itself on inclusion, and the student body and faculty “thrive on student-centered education and fostering personal and intellectual growth to prepare students for productive careers, meaningful lives, and responsible citizenship in a global society.”

The university’s dedication to growth goes beyond its current students and into its larger local community. With the institution having a strong and historic relationship with the Saginaw Chippewa Indian Tribe, the partnership allows for the advancement and improvement of community members’ quality of life. With Native Americans being underrepresented at major points in the academic data science pipeline, it speaks volumes that the university is seeking collaboration to engage with high school students early in their career planning and help them understand potential career paths in data science.

Mohamed Amezziane
Mohamed Amezziane

After seeing the lack of programming geared toward at-risk high school students in the community, CMU faculty members, Dr. John E. Daniels and Dr. Mohamed Amezziane developed a proposal to create a data science workshop for high school students from underrepresented and tribal communities. Daniels and Amezziane stated, “We wish to target students who are unsure about their future but might not be considering college due to financial issues or uncertainty in a major. Often, these students come from underrepresented groups and are overlooked as potential university students.”

With support from the MBDH, CMU will partner with several high schools in rural central Michigan to offer a 5-day summer workshop at CMU, introducing approximately 35 rural and underrepresented high school students to data science. Participants, including student members of the local Ojibwa Tribe, will be recruited with the support and recommendations of their local high schools.

Upon completion of the workshop, students will be more familiar with data science, will analyze data using open-source statistical software (R), and will learn how to prepare and give a professional presentation summarizing their assigned research project. The context of the assigned learning modules and project will be on making healthy lifestyle choices (nutrition, alcohol/drugs). Data used in the workshop will come from selected sources, such as the National Health and Nutrition Examination Survey (NHANES). According to the website, NHANES is a resource that consists of demographic, socioeconomic, dietary, and health-related questions designed to assess the health and nutritional status of adults and children in the United States.

Central Michigan University’s Data Science program was started 18 months ago and is attempting to generate interest among the local student population. The flexibility and versatility of data science provide an opportunity to attract and recruit students who might not fit the typical college-prep template. Not only does the program hope to foster students’ interest in data science but the CMU Admissions staff will also offer assistance to students on how to apply to data science programs, fill out Free Application for Federal Student Aid (FAFSA) financial aid forms, and address possible application barriers that would prevent students from completing a successful admission application.

Through best practices and student feedback from this 5-day program being evaluated, there are plans to make this a yearly event. Overall, the university hopes to see an increase in the number of students pursuing Data Science as a major at CMU or other regional colleges and universities. In addition, by personalizing the data sets, Daniels believes the students will connect how using statistical software could be used to make better decisions in their own lives.

John Daniels
John E. Daniels

Our workshop will focus on making healthy lifestyle choices,” Daniels said. “Instead of preaching about smoking, drinking, or texting while driving, we hope to use data science as a vehicle to demonstrate the consequences of one’s lifestyle choices and at the same time learn about all of the tools and techniques data science has to offer. The methods we will be teaching can be applied to a variety of research questions and data sets. Perhaps this will inspire some students to recognize the value of data science and to pursue it in higher education.”




Joseph (Jeff) Inungu
Joseph (Jeff) Inungu

Dr. Jeff Inungu, CMU Professor and Director of the Master of Public Health Program, believes that by using the lens of public health and data science, “Experience and integrative learning offer students opportunities to gain skills that are highly desirable and prepare them to become leaders who are able to meet the ever-changing challenges of promoting, protecting, and enhancing the health of vulnerable communities.”

Regarding the long-term goals for the workshop, Daniels says, “Overall, the program will continue to focus on data science, reinforce the healthy lifestyle context, and gradually increase the number of workshop participants. The desired outcome is a steady increase in data science majors in our geographic area.”

When the workshop concludes, the team will work with the MBDH to assess the impact of the project and make resources available for faculty at other institutions to use in developing similar events on their campuses.

Get Involved

This work is supported by the National Science Foundation through the MBDH Community Development and Engagement (CDE) Program.

Contact the MBDH to learn more, or if you’re aware of other people or projects we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Data Science for the Public Good Young Scholars Program

By Isabel Alviar

Data is the new science; it has the potential to answer the world’s problems if the right questions are asked. And some data science education programs are now focusing on working with local communities to help with real-world problems.

The Data Science for the Public Good (DSPG) Young Scholars Program is an immersive summer program that engages students from across Iowa to work together on projects that address social issues in the world today. Both graduate and undergraduate students are selected through a competitive statewide search. Graduate students (fellows) lead, support, and guide students together with Iowa State University (ISU) faculty and research associates, while undergraduate students (interns) acquire programming and statistical analysis experience through formal training and practical applications.

Working in teams, fellows and interns collaborate with project stakeholders and research faculty across disciplines. Research teams combine disciplines including statistics, data science, and the social and behavioral sciences to address complex problems proposed by local, state, and nonprofit agencies. Some of the program highlights for scholars include: expert training in tools for quantitative computing and data visualization (R, GIS, Tableau, etc.); professional training through workshops, seminars, and career talks; individualized mentors working closely with students; technical reporting and publication opportunities; and opportunities to interact with decision-makers in local communities, nonprofits, and state government agencies.

This past summer’s DSPG Program ran from May 23 to August 5. In light of COVID-19 and to accommodate non-ISU students, the program was held entirely online. Nonetheless, DSPG Scholars were provided the same opportunities to develop a professional portfolio, expand their networks, and learn about practical applications of data science to solving real-world problems. At the end of the summer, scholars got to present their research at the Annual DSPG Symposium. The symposium featured several distinguished keynote speakers and poster presentations by the Young Scholars. Final presentations for the 2022 DSPG Program were held on Thursday, August 4 via Zoom and recordings are available on ISU’s website.

The program is led every year by five land-grant universities and funded, in part, by the US Department of Agriculture (USDA) National Institute of Food and Agriculture (NIFA) to create a coalition for the public good. Christopher Seeger, one of the professors leading Iowa State’s program, said, “Ultimately, this is a community service. We let the community drive the conversation, while we listen to what they want and how we can help.” All of the projects were built upon a model called the Community Learning through Data Driven Discovery Process (CLD3), and helped local communities tackle real problems. Projects were incredibly diverse, with topics ranging from wholesale local food benchmarking to evaluating indicators for equal local housing needs to creating interactive commodity reports for agricultural marketing.

A webinar that further highlighted some of these projects and the DSPG Program was hosted by the Midwest Big Data Innovation Hub on October 27, 2022. Matthew Voss, Rural Policy Data Analyst for the Public Science Collaborative, featured a project from his summer as a graduate fellow where his team created analytics and dashboards to help a nonprofit organization, Eat Greater Des Moines (EGDM), more effectively target, locate, and expand food rescue in Central Iowa. Their client came to them because they had an abundance of data but did not know how to use it to answer crucial questions posed by their board, such as where people are experiencing the most food insecurity, which distribution sites have the greatest losses due to food waste, etc. This is where the DSPG Scholars stepped in. For their project, the students cleaned the large data sets and then used them to develop sustainable pipelines in Google Sheets and Google Data Studio that visually answered EGDM’s questions through interactive dashboards. The project is now published on the nonprofit organization’s website, where the DSPG team is directly credited for all of their work.

Voss’s project was just one example of how the DSPG Young Scholars Program is making a positive impact on the community while also teaching students valuable data science skills. Two other DSPG fellows, Kelsey Van Selous and Harun Çelik, also presented their projects on the webinar. Dr. Cassandra Dorius, Associate Professor of Human Development and Family Studies, and a founding co-director of the DSPG Program, said, “Students were very creative and motivated, and produced great analytics and projects. We are excited to see how this work improves people’s lives moving forward.”

Get Involved

Contact the MBDH to learn more, or if you’re aware of other people or projects we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Unmanned Aerial Systems, Plant Sciences and Education (UASPSE) Project Featured in Special Section of Agronomy Journal

The Digital Agriculture community of the Midwest Big Data Innovation Hub (MBDH) achieved a major milestone this week with a series of open-access publications on ag data.

The Unmanned Aerial Systems, Plant Sciences and Education (UASPSE) project, funded by an award from the National Science Foundation’s Big Data Spokes program (NSF award 1636865), wrapped up its activities this month with the publication of nine open-access articles in the September/October 2022 issue of Agronomy Journal under the Special Section: Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy (BDPO).

Special Section topics include:

Two long-time MBDH team members played important roles in producing the special section: MBDH Site Coordinator Aaron Bergstrom, PI on the UASPSE project and Advanced Cyberinfrastructure Manager at the University of North Dakota; and Jim Wilgenbusch, Co-PI on the MBDH award and Director of Research Computing at the University of Minnesota.

The BDPO special section consists of a series of articles based on presentations given at the June 24, 2020, Virtual Workshop on Big Data Promises and Obstacles: Agricultural Data Ownership and Privacy. The Digital Agriculture: UASPSE Spoke project of the MBDH, together with the University of Minnesota College of Food, Agricultural and Natural Resources Sciences and PepsiCo, hosted the workshop, which focused on data ownership and privacy as it relates to academic and industry research and development in agriculture. The workshop was originally scheduled to be co-located at the US Agricultural Information Network (USAIN) Biennial Annual Meeting that was to be held in Lubbock, Texas, on May 1, 2020. However, the COVID-19 pandemic caused the in-person USAIN meeting to be postponed. The BDPO workshop organizers then decided to host the BDPO workshop separately as a virtual workshop in June of that year via Zoom.

A total of 210 persons registered for the virtual workshop. While many attendees came and left throughout the day, the maximum attendee count during the event reached 142 active attendees. Because the event was virtual and the speakers represented groups with an international presence, there were attendees from North America, Europe, Africa, Asia, and Australia.

In addition to 11 invited presentations, two breakout discussion sessions were held on topics chosen based on the 117 responses to the pre-workshop survey. A short post-workshop survey was conducted as well, with 116 respondents, to gather data on breakout sessions in which the attendees participated.

The 11 virtual workshop presentations are available via YouTube.

Get Involved

Interested in ag data? The Midwest Big Data Innovation Hub (MBDH) co-leads a new working group sponsored by the Institute of Electrical and Electronics Engineers Standards Association (IEEE SA) to understand agricultural data needs across the food supply chain. Join the kickoff workshop on December 5, 2022, in Champaign, Illinois.

Contact the MBDH to learn more, or if you’re aware of other people or projects we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Meet the MBDH 2022–2023 science communications and outreach interns

For Fall 2022, the Midwest Big Data Innovation Hub (MBDH) has four new interns joining the team to work on a variety of projects. One intern, Shruti Ravichandran, is focused on outreach to help build our student community platforms. Three others, Aisha Tepede, Isabel Alviar, and Sasha Zvenigorodsky, will be focused on science communication, helping to tell the stories of our collaborators and amplify the many community-led data science projects in the Hub’s 12-state region. All will learn about the range of activities and communities the MBDH is involved in, will receive mentoring, and will have opportunities for career development. Below are details on the great backgrounds and interests the students bring to the MBDH community.

Aisha Tepede

Aisha Tepede (she/her) is a Science Communications Intern at MBDH this semester. She is a second-year Master of Public Health (MPH) student in the College of Applied Health Sciences at the University of Illinois at Urbana-Champaign (UIUC). She will be graduating this December with a concentration in Health Promotion and Education. Aisha has previously worked with Cook County Health as a case investigator for COVID-19 and with the National Institutes of Health as a clinical research fellow, focusing on a rare disease called multiple endocrine neoplasia type 1.

She has a social and behavioral health background involving chronic diseases and underrepresented populations. With this interest, she branched out into the global health research realm. She had the opportunity to spend the summer in Kenya by participating in the Minority Health and Health Disparities Research Training Program (MHRT) funded by National Institute on Minority Health and Health Disparities (NIMHD), where she spent time researching sexual and reproductive health training with adolescent students.

Long term, Aisha has a goal of becoming a public health physician-scientist. She states, “I plan to use my experiences and background to be able to improve communication between physicians and marginalized patients—whether that means patients with a rare disease or a part of an underserved community.” Apart from her aspiration for proper clinician and patient communication, she says “I envision myself as a physician who will actively engage in improving the health of underserved populations, through a combination of community health research and culturally sensitive approaches to medicine and patient care.”

Isabel Alviar

Isabel Alviar is joining MBDH as a Science Communications Intern this semester. She is a senior at UIUC studying Computer Engineering with a minor in Statistics. Next year, she plans on pursuing her master’s degree in Computer Science, specializing in either artificial intelligence or data science. Currently, she is developing parallel-computing machine problems for programming classes at UIUC, and analyzing and summarizing data for an engineering education research conference.

Isabel is interested in pursuing a career that revolves around using data, whether as a software engineer or data scientist/analyst. This summer, she worked at Procter & Gamble (P&G) as a software engineer intern in their Data & Analytics department, automating the process of importing and updating metadata between objects in data platforms to a central Data Catalog. She also pitched the idea of a smart chatbot for the catalog and created a prototype using artificial intelligence/machine learning (AI/ML) that will continue being implemented by P&G based on her code and research.

She believes that the work being done by the Midwest Big Data Innovation Hub is exciting and inspiring. Isabel hopes to use her passion for science and technology to bring people’s stories, research, and scientific discoveries to life through writing. One of her favorite quotes is, “The science of today is the technology of tomorrow.”

Sasha Zvenigorodsky

Sasha Zvenigorodsky is joining MDBH this semester as a Science Communications Intern. As a senior at UIUC, Sasha is pursuing a BS degree in Crop Sciences. Outside of class, Sasha has been conducting research with UIUC’s Small Grains Improvement lab under Dr. Jessica Rutkoski, studying the correlation between vernalization and overall grain yield of winter wheat.

As a scientific researcher herself, Sasha is conscious of the important intersections between science and writing. Sasha says, “A major part of scientific research is the process of converting it into a language that can be easily understood by both experts and nonexperts alike.” Through writing, she hopes to make new scientific findings and developments more accessible to the public.

Sasha aspires to use her own experience working within a STEM field as well as her passion for creative writing to raise awareness for new innovations and findings in science. “Ultimately, giving individuals the right tools to stay educated and aware is the best way to catalyze positive change in society today,” she says.

Shruti Ravichandran

Shruti Ravichandran is joining MBDH as a Project Coordination Intern in Fall 2022. She is a first-year master’s student majoring in Information Management.

She gained interest in the field of data during her undergraduate degree in Electronics and Telecommunication Engineering, while researching about this field online to write an article for a technical magazine published by her school. She began building her skill set in analytics and landed a job at ZS Associates, India, as a Decision Analyst after she graduated in 2020. At ZS, she worked in the healthcare vertical on several big data analytics and data science projects in therapy areas such as leukemia, multiple sclerosis, and glaucoma. These experiences brought her the realization that information management has immense potential to influence actions and decisions that make the world a better place. She aspires to work on such endeavors during her career as a data professional.

She sees working at the Midwest Big Data Innovation Hub as a huge opportunity for her to give back to the community of data professionals by bringing together student groups across the region that are interested in this field. Her goal is to help build a community of data enthusiasts that understand the power of analytics, the responsibility they have to uphold the ethics of handling information, and the positive change that it can bring in a wide range of fields such as education, agriculture, and healthcare, among others.

Iishi Patel

Iishi Patel is joining MBDH as a Science Communications Intern for Spring 2023. She is in her second semester in the graduate program of Master of Science in Information Management at the University of Illinois at Urbana-Champaign. She is specializing in Data Science and Analytics and is looking forward to pursuing a career as a data scientist.

Iishi has experience working in data teams of various industries such as travel and tourism, electronics, and telecommunications. She also has research interests in graph neural networks and network security themes. She believes that with the rise of artificial intelligence technologies, we can achieve great automation as well as strength in the field of network and cyber security. Her previous work was to detect DNS over HTTPS (DoH) tunneling [which encrypts Domain Name System (DNS) traffic by passing DNS queries through a Hypertext Transfer Protocol Secure (HTTPS)-encrypted session] using deep neural networks. She is also an incoming Data Engineering Intern at Tesla with the Vehicle Safety and Homologation team this summer.

She believes “Data is a magnetic component to drive the world and its humankind into a path of refinement” and working with the Midwest Big Data Innovation Hub is a great opportunity for her to combine her passion for writing with the field of her interest (i.e., data science and security). Iishi hopes to bring forward great stories to inspire people in the field of technology and create an awareness of the latest trends in it.

MBDH Executive Director John MacMullen said, “We’re excited to be able to continue this intern program for another year. The incoming students bring diverse experiences and a wide range of interests. We look forward to having the MBDH community engage with them to tell the stories of the innovative work happening across the region.”

The MBDH has a number of events planned for Fall 2022, including our ongoing webinar series: the Collaboration Cafe, Midwest Carpentries Community, and Data Science Student Groups series, and the Water Data Forum, all open to participation from people across the region.

Get involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in our activities, which include a data science student community.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

National Workshop on Data Science Education Featured Multiple Hub Talks

Kim Bruch, West Big Data Innovation Hub Science Writer

Organized by UC Berkeley’s Division of Computing, Data Science, and Society, with support from Microsoft and the West Big Data Innovation Hub, the Summer 2022 National Workshop on Data Science Education offered an array of insight about current data science education initiatives across the academic spectrum, from high school to undergraduate and graduate level programs as well as adult learners.

The latter two days of the workshop focused on national perspectives and programs for data science education, including student driven data science communities of support and learning. The National Science Foundation (NSF) Big Data Innovation Hubs hosted two panels alongside a program of presenters that discussed topics such as investigating the ethics behind algorithms, incorporating Python into statistics and computer science classes, and the latest developments in data science education and community building.

“The West Hub was happy to coordinate the NSF Big Data Hubs’ contribution to this workshop,” said West Big Data Innovation Hub Executive Director Ashley Atkins. “It was an opportunity to share with a national audience some of the undergraduate-focused work the Hubs are pursuing across the country.”

Many lessons learned were discussed during the NSF Big Data Hub panel entitled “Building National Capacity for Student-Driven Data Science Communities.” The panel was moderated by Northeast Big Data Innovation Hub Executive Director Florence Hudson and included presentations by John MacMullen, Emily Rothenberg, Scott Blender, Abhishek Sinha and Rajeev Bukralia.

“The National Student Data Corps began as a grassroots effort in the Northeast region in 2021, and grew to nearly 3,000 community members by June 2022 across the U.S. and in 20 countries around the world,” said Hudson. “Students, professors, industry and nonprofit data science professionals worked together to build this dynamic community of support to increase data science awareness and provide free open online data science resources for students and educators, along with data science career panels, mentoring via a 500-person slack channel, career and chapter resources. We are working together to democratize data science for all.”

Temple University Engineering and Data Science Student Scott Blender talked about the National Student Data Corps (NSDC) from a student perspective—focusing on goals of the chapter systems. He said that their aim is “to inspire, educate, and serve local communities with professional development opportunities by leveraging NSDC resources and events.”

A similar student-aimed program discussed was the Midwest Big Data Innovation Hub’s Data Science Student Groups Community. Rajeev Bukralia, professor at Minnesota State University, Mankato, also spoke about his development of the Data Resources for Eager and Analytical Minds (DREAM) student group, which is the largest registered student organization on campus, and brings data science perspectives to students from many disciplines. Details about both DREAM and NSDC can be found on their respective websites.

“We are focused on building a group of student leaders to share best practices about how to grow inclusive, multi-disciplinary student organizations,” said Executive Director of the Midwest Big Data Innovation Hub John MacMullen. “Learning from more established groups such as DREAM can help newer student organizations understand how to build strong, diverse teams with engaged participants.”

Another great NSF Big Data Hub Panel at the workshop was entitled Data Science Program Development. South Big Data Hub Executive Director Renata Rawlings-Goss of Georgia Tech opened the panel with a thorough explanation of how they developed their data science education efforts.

West Hub principal investigator Jennifer Chayes gave an overview of Berkeley’s Division of Computing, Data Science, and Society (CDSS), where she serves as associate provost.

Eric Van Dusen speaking during a panel discussion. Photo by KLCfotos.
Workshop organizer Eric Van Dusen, outreach and technology lead for the Data Science Undergraduate Studies program, speaks during a panel discussion. (Photo/ KLCfotos)

“This is the fifth annual conference and the West Big Data Hub has always been a key partner-stakeholder in convening folks in this space. It was great to have multiple hubs collaborating to share so many perspectives,” said CDSS Technology and Outreach Lead Eric Van Dusen, who organized the workshop.

New Precision Agriculture Initiatives in the Midwest

By Raleigh Butler

Recently, there has been a large amount of U.S. federal funding directed toward next-generation precision-agriculture initiatives. This article summarizes a few such projects based in the Midwest.

I-FARM

A new project called I-FARM was recently awarded funding by the USDA’s National Institute of Food and Agriculture (NIFA) in May 2022 under the “Farm of the Future” program. The Illinois Farming and Regenerative Management project will focus on sustainability in farming practices. I-FARM, led from the University of Illinois, is a collaborative study across the Institute for Sustainability, Energy, and Environment (iSEE) and the Center for Digital Agriculture (CDA), which is based at the National Center for Supercomputing Applications (NCSA). The project, funded with $3.9 million in grant money, is planned to last three years. For this very competitive program, only one project across the nation received funding.

According to the NIFA website, “The Farm of the Future Program integrates advances in precision agriculture, smart automation, resilient agricultural practices, socioeconomics, and plant and animal performance.”

The I-FARM project will focus on bettering these aspects of agriculture. Of course, as the world changes due to climate change and pollution, sustainability is an area of increasing concern. “Together, this integrated suite of solutions will lead to sustainable ways of meeting growing demand for agriculture in a changing climate,” said Co-PI and iSEE Interim Director Madhu Khanna, the Distinguished Professor of Agricultural & Consumer Economics at the University of Illinois.

I-FARM was seed-funded by iSEE’s “Campus as a Living Laboratory” program and now has received the grant from USDA NIFA. During the three years, the 80-acre I-FARM test bed “will feature improved precision farming with remote sensing; new under-canopy autonomous robotic solutions for cover-crop planting, variable-rate input applications, and mechanical weeding; and artificial intelligence-enabled remote sensing for animal health prediction, nutrient quantification, and soil health.”

AIFARMS

Other recently funded projects focus on leveraging artificial intelligence (AI) to benefit agricultural research and translations of this work to impact practitioners and communities. One project is AIFARMS, or “Artificial Intelligence for Future Agricultural Resilience, Management, and Sustainability.” Led by PI Vikram Adve in the Center for Digital Agriculture at the National Center for Supercomputing Applications, AIFARMS “covers autonomous farming, efficiency for livestock operations, environmental resilience, soil health, and technology adoption.”

ICICLE

The ICICLE project combines elements similar to those of both I-FARM and AIFARMS. Led by The Ohio State University (OSU), the institute’s acronym stands for “Intelligent Cyberinfrastructure with Computational Learning in the Environment.” The project will integrate AI (like AIFARMS) but focus primarily on crops and soil. It will use technology such as field sensors to help maximize agricultural production. According to an OSU article, “The institute (led by Dhabaleswar K. Panda) will build the next generation of cyberinfrastructure with a goal of making AI data and infrastructure more accessible to the larger society.”

AIIRA

AIFARMS, ICICLE, and a third project, AIIRA, were all funded under the NSF AI Institutes program, which includes a partnership with the USDA’s National Institute of Food and Agriculture (NIFA), which is providing the funding for the AIIRA project. AIIRA is the “AI Institute for Resilient Agriculture,” and includes stakeholders from academia, government, and industry. Led by PI Baskar Ganapathysubramanian from Iowa State University, the project has a vision “to create new AI-driven, predictive digital twins for modeling plants, and deploy them to increase the resiliency of the nation’s agricultural systems.”

All of these projects demonstrate high interest across sectors in precision-agriculture innovations that can make the transition from academic research labs and demonstration projects to deployment at scale for agricultural production that can meet the country’s changing needs.

Get Involved

The Midwest Big Data Innovation Hub (MBDH) co-leads a new working group sponsored by the Institute of Electrical and Electronics Engineers Standards Association (IEEE SA) to understand agricultural data needs across the food supply chain.

Contact the Midwest Big Data Innovation Hub to learn more, or if you’re aware of other people or projects we should profile here. We invite participation in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Toward Building Quality Relationships: How Chatbots Can Help Us Practice Self-Disclosure

By Qining Wang

Under the turmoil of social events, from global pandemics to wars and social unrests, mental health is becoming an increasingly greater concern among the public.

According to the Anxiety and Depression Association of America (AADA), anxiety disorders are the most common mental illness in the USA, affecting 40 million adults. Another common mental health illness, depression, affects 16 million adults in the USA, according to statistics from the Centers for Disease Control and Prevention (CDC). The greater awareness and gradual destigmatization of mental health issues have led more people to seek professional help to improve their overall mental well-being.

When working with mental health professionals, self-disclosure is vital to finding the roots and triggers of mental health issues. Self-disclosure is a process through which a person reveals personal or sensitive information to others. It is a crucial way to relieve stress, anxiety, and depression.

Meanwhile, self-disclosure is a skill that one needs to cultivate through practice. It’s a skill we can only practice through constant self-exploration and the courage to be vulnerable.

To investigate alternative ways of practicing self-disclosure, a research team at the University of Illinois at Urbana-Champaign (UIUC) explored chatbots and conversational AIs as potential mediators in the self-disclosure process in a study in 2020. The team leader, Dr. Yun Huang, is an assistant professor in the School of Information Sciences at UIUC and the co-director of the Social Computing Systems (SALT) Lab. The team is mainly interested in context-based social computing system research.

Chatbots are ubiquitous in today’s online world. They are computer programs interacting with humans back-and-forth, like having a conversation. Some chatbots are task-oriented. An example can be a frequently-asked-questions (FAQ) chatbot that recognizes the keywords a person types and spits out a preset answer according to the keywords. Other more sophisticated chatbots, such as Apple’s Siri and Amazon’s Alexa, are data-driven. They are more contextually aware and can tailor their responses based on user input. Both are ideal qualities for designing an empathetic and tone-aware chatbot capable of self-disclosure.

As such, Dr. Huang’s team built a self-disclosing chatbot that can engage in conversation more naturally and spontaneously. The chatbot would initiate self-disclosure during small-talk sessions. It would gradually move to more sensitive questions that encourage users to self-disclose.

To study how chatbots’ self-disclosure can affect humans’ willingness to self-disclose, the team recruited university students and divided them into three groups. Each group would interact with the chatbot at different levels of self-disclosure, from no self-disclosure to low and high levels of self-disclosure.

During the four-week study, the student participants would interact with the chatbot every day for 7–10 minutes. At the end of the third week, the chatbot would recommend that students interact with a human mental health specialist. The researchers would then evaluate students’ willingness to self-disclose to the professional.

The team found that the groups that self-disclosed to the chatbot reported greater trust in the mental health professional than the control group. Participants felt “confused” when the chatbot brought up the human professional. In the experimental groups, they felt that they could listen to the chatbot and share sensitive experiences.

The team noted that, for participants interacting with the chatbot with the highest level of self-disclosure, their trust for the mental health professional stemmed from the trust of the chatbot. Participants’ trust was mainly directed toward the research team and professionals behind the chatbot for the other two groups.

This study highlights how chatbots can be a great tool to help users practice self-disclosure, making them more comfortable seeking human professionals. It is worth noting that, regardless of how sophisticated chatbots can be, they are just mediators between users and mental health professionals.

At the end of the day, the most meaningful kind of self-disclosure can only be found through care, empathy, and understanding. Human to human.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Physics-Based Machine Learning for Sub-Seasonal Climate Forecasting

By Raleigh Butler

We’ve all heard the old adage that if you don’t like the weather in the Midwest, wait a minute and it will change. So how can we possibly forecast conditions weeks in advance?

In 2019, an NSF collaborative grant was awarded to six institutions to sponsor the study of sub-seasonal climate forecasting (SSF)—with machine learning (ML). This topic addresses three core themes of the Midwest Big Data Innovation Hub—resilient communities, digital agriculture, and cyberinfrastructure. A project of the NSF Harnessing the Data Revolution (HDR) program, this award was to researchers at the following six universities: University of Minnesota–Twin Cities, University of Chicago, University of Wisconsin–Madison, Carnegie Mellon University, George Mason University, and the University of Illinois at Urbana-Champaign.

What is Sub-Seasonal Climate Forecasting?

Sub-seasonal climate forecasting focuses on predicting weather 2–8 weeks away. Interestingly, this is an area of higher difficulty than other types of forecasting. As the research team states on its website, “SSF is considered more challenging than either weather forecasting or even seasonal forecasting.” This effort ties ML together with agriculture in an effort to make these difficult predictions.

Computing’s Place in Forecasting

What is ML compared with deep learning (DL)? Machine learning builds methods for machines to “learn” or change their procedures based on input over time. Deep learning is a specific type of ML and is based on how the human brain operates.

In the linked article below from the SSF team, some difficulties in building models are discussed. Many of these difficulties are tied to the relationship between ML and physics. Therefore, systems have been created for physics-guided ML and ML-enhanced physics. Here’s what some of these systems take into account to overcome the difficulties:

  • • Physics-guided ML takes physics into account to produce output (such as forces affecting movement of clouds, gravity in rainfall, etc.). Unfortunately, existing data that includes physics-related information is limited.
  • • The other approach is ML-enhanced physics. One example of this, among many, is the Monte Carlo Tree Search (MCTS). The MCTS works by applying a hierarchical partition tree to the data. By using this approach, the program follows the sub-“branches” that are most likely in a given situation to produce a prediction. In short, the MCTS works as a decision tree and is optimized to predict the most likely path down each branch with each decision. A visual is provided in the image below.

Drawing of a decision-tree flowchart. Photo by Kelly Sikkema.
Credit: Unsplash, Kelly Sikkema

Sub-Seasonal Agriculture

How does this tie into agriculture? First, we will examine the key planning that takes place during sub-seasonal periods. According to a graph on the SSF project site, these are some important decisions that are made during those periods:

  • Maritime Planning: Designate ship routing
  • Agriculture: Schedule planting
  • Agriculture: Irrigate and apply nutrients
  • Emergency Management: Pre-stage emergency supplies
  • Aviation: Plan evacuations and sorties
  • Water Resources: Manage reservoir levels for flood control
  • Energy: Plan for spikes in energy demand

Making these decisions is a delicate process; there is a high price to pay if predictions are incorrect. Increasing the ability to accurately forecast sub-seasonally is, of course, monetarily valuable; however, it is also valuable in terms of product production and delivery.

These studies have resulted in several scientific publications since the conclusion of the funding. One of these papers, published by many team members of the original study, is published here (available for download as a pdf). The paper, published in June 2020, discusses challenges, analyses, and advances associated with ML climate forecasting. The paper includes several diagrams of how various models predict sub-seasonal weather differently. The models also discuss forecasting in various climate zones (over the ocean, and different areas over land).

Scientists are still collecting data to use as input for the models and to increase accuracy. As mentioned, this area of forecasting is more difficult than forecasting over time horizons that are nearer or further away. Although climate prediction may still be difficult, there is progress being made in the field. The paper mentioned above states, “Overall, XGBoost and Encoder (LSTM)-Decoder (FNN) perform the best. Qualitatively, coastal and south regions are easier to predict than inland regions (e.g., Midwest).”

Get Involved

Learn more about the SSF project on their site.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities. The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Building an accessible agricultural data community with the National Agricultural Producers Data Cooperative

By Raleigh Butler

Romaine lettuce crop grown on a city farm in Moscow. Photo by Petr Magera.
Photo by Petr Magera/Unsplash

Entities around the world gather data focused on various aspects of agriculture. Unfortunately, this information is not always accessible or easily available for those who need it. The National Agricultural Producers Data Cooperative (NAPDC) project recognizes that agriculture is a keystone of society and a critical piece of national solutions to climate-related challenges. The NAPDC, with support from the United States Department of Agriculture (USDA), aims to enable agricultural producers to benefit from the massive amounts of data generated by members of their community. As the NAPDC site states, the goal of the project is to create a “blueprint” for a national data framework where agricultural entities “can store and share data . . . to maximize their production and profitability.”

With enough available data and methods to extract relevant information, national agricultural systems can become more efficient and profitable. The framework being developed by the NAPDC will include data from many types of agricultural contexts and agricultural institutions, first and foremost the producers that drive agricultural productivity. Making the system diverse yet robust while safeguarding farmer privacy will result in a more reliable set of data for the entire agricultural community.

The NAPDC project emphasizes providing resources to community partners through webinars and seed grants in order to “identify needs and opportunities as well as challenges in physical infrastructure, education and human resources, and critical use cases” critical to the success of a future data framework. The project recognizes that a secure framework is necessary to protect privacy and governance information; these aspects will be carefully considered. The project also recognizes the importance of land-grant institutions and agricultural extension in the successful deployment of any framework.

The NAPDC project has a seed grant program to support development of community activities, with a deadline of June 1, 2022. It will be granting 4–6 awards; complete guidelines are listed on the site here. The grants will not be limited to principal investigators at universities; rather, any institution eligible for USDA funding may apply. As stated on the website, “individuals willing and qualified to lead representation for a national or regional agroecosystem are encouraged to apply.”

“The work of the NAPDC aligns well with the Digital Agriculture community of the Midwest Big Data Innovation Hub,” said MBDH Executive Director John MacMullen. “We anticipate integrating findings from our Community Data Needs Assessment (Community DNA) activities, which are helping to understand the data needs of stakeholders across the food supply chain, with the work of the NAPDC. We also look forward to partnering with the NAPDC team on our agricultural data work with the IEEE Standards Association and other partners.”

Jennifer Clarke, lead PI of the NAPDC project and faculty at the University of Nebraska–Lincoln, hopes the project serves as an initial step towards a national framework. “This project represents the willingness of the USDA to listen to agricultural producers and support the data needs of producer communities,” said Dr. Clarke. “This project provides producers and stakeholders with a vehicle for communicating their challenges related to data, and provides educators and researchers with a vehicle for proposing solutions to these challenges.”

The NAPDC will host an All-Hands Meeting in the spring of 2023 at the University of Nebraska–Lincoln that will highlight the work of the NAPDC and discussions of specific areas for future USDA investment. Interested members of the community can sign up for the project listserv through the project website (https://www.agdatacoop.org/) to receive updates about this meeting as well as project information.

Get involved

Do you have an agricultural data success story or case study to share from your organization? Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

I-GUIDE: Increasing Sustainability by Harnessing Data

By Raleigh Butler

Gravity dam in Marion County, Oregon. Photo by Dan Meyers.
Photo by Dan Meyers/Unsplash

Sustainability is not just achieved through solar panels and windmills. Of course these help, but one organization is working to tackle sustainability on a larger scale: I-GUIDE is a collaborative environment for sharing and using geospatial data. It is community-oriented and works to address sustainability challenges.

“I-GUIDE” stands for “Institute for Geospatial Understanding through an Integrative Discovery Environment.” This project is funded by the National Science Foundation (NSF) under the Harnessing the Data Revolution program. Awarded in 2021, the institute is led by PI Shaowen Wang, head of the Department of Geography and Geographic Information Science at the University of Illinois. The institute has partners from across the country, including MBDH collaborators such as EarthCube, CUAHSI, the University of Minnesota, Columbia University, and the Discovery Partners Institute.

As the I-GUIDE site states, “most challenging sustainability and resilience problems today require expertise from multiple domains and geospatial data science.” I-GUIDE acts as a main point for qualified entities to access varying types of data. For example, I-GUIDE allows other participating entities to access the data stored in HydroShare, a system from CUAHSI, the Consortium of Universities for the Advancement of Hydrologic Science, Inc. The HydroShare infrastructure can be used to share data as well as analyze and visualize those data. I-GUIDE brings together other related programs. This allows increased knowledge on the subjects of sustainability, and the supporting data. I-GUIDE currently has data being added to it in the fields of water, geospace, geography, and the atmosphere.

“The institutional collaborations facilitated by this project will enable the I-GUIDE team as well as the broader community to explore a wide range of interdisciplinary science questions that leverage an interconnected network of software and cloud infrastructure,” said Dr. Anthony Castronova,
Senior Research Hydrologist at CUAHSI. “These types of institutional connections are critical to support water science research around pressing environmental issues that require modern software, data, and modeling approaches.”

Environmental issues often present themselves in one way (e.g., a drought) when the problem at hand is much larger than the assumed cause (a lack of rainfall). As the climate changes, droughts and other environmental changes can become increasingly harmful to current ecosystems. HydroShare cultivates collaboration in water-focused areas such as drought conditions, water quality, temperature, and soil moisture. These data act as the first step to help promote sustainability and resilience.

I-GUIDE holds regular webinars. The first in the series, held on March 23, 2022, explored the need for geospatial education when sustainability is growing more important every day. Led by Eric Shook from the University of Minnesota, the webinar emphasized the need for building diverse communities of instructors and learners to build best practices for cyberinfrastructure (CI) literacy, and lower the barriers for learners new to CI.

“The Midwest Big Data Innovation Hub is pleased to be a partner on the I-GUIDE project,” said MBDH Executive Director John MacMullen. “This is a diverse and talented team that will have important impacts on key areas of focus for the MBDH, including water data, CI workforce development, and data-enabled resilient communities.”

“MDBH is a great example of how our I-GUIDE Partners are organizations and institutions that share common goals and objectives,” said George Percival, co-lead of I-GUIDE’s Engagement and Partnership Team. “The I-GUIDE Partnership Program provides the pathway for Partners to contribute to and gain from the I-GUIDE activities based on mutually beneficial agreements. As the MBDH objective “to build and cultivate communities around data” is highly aligned with I-GUIDE, it is anticipated that the MBDH and I-GUIDE partnership will benefit both activities.”

If you’re interested in getting involved with I-GUIDE, please take a look at their News & Events page. The site often lists such events as webinars and symposiums. The I-GUIDE team held its first All-Hands Meeting in May 2022.

Get Involved

Activities to build the community of Midwest researchers and practitioners in the Smart & Resilient Communities priority area of the Midwest Big Data Innovation Hub are continuing throughout 2022. Contact the Hub if you’re interested in participating, or are aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Exploring Nature Through Imageomics with Professor Tanya Berger-Wolf

By Erica Joo and Qining Wang

We recently spoke with Professor Tanya Berger-Wolf, a pioneer in the area of imageomics who is leading a team to start a new field of imageomics. She is a computational ecologist who is director and co-founder of the nonprofit organization “Wild Me.” Berger-Wolf is also the Director of the Translational Data Analytics Institute (TDAI) and a Professor of Computer Science Engineering, Electrical and Computer Engineering, as well as Evolution, Ecology, and Organismal Biology, at The Ohio State University.

Tanya Berger-Wolf

Observation is fundamental to any biological research. The development of optics technology, such as the inventions of the microscope and the telescope, allowed biologists to observe the world at different scales, from animals living in jungles of millions of acres to DNA in animal cells of several micrometers.

However, as Prof. Berger-Wolf pointed out, those inventions only serve to “augment our ability to look” or “look at more things more carefully.” We are still making observations and searching for patterns with our own eyes, from which arises the caveat: We are not so good at finding patterns when things appear to be random, or when patterns are rare, sparse, subtle, or complex. We can’t answer, for example, whether the stripe patterns of mother zebras are similar to their babies’. The patterns appear to be too similar and too random at the same time to our eyes because human brains did not evolve to “take [the stripe patterns] holistically and quantify them in any meaningful way.”

And that’s where imageomics comes in. Imageomics is following genomics, a field where researchers understand the biology of an organism or a species through their genetic information. In a similar vein, imageomics aims to understand nature through biological information extracted from images.

Computers are the perfect information extractors, because they “perceive” the world differently. Computers can quantify images down to pixels and find patterns that humans do not, or cannot, comprehend. Berger-Wolf pointed out that imageomics, as a “whole new field of science,” allows scientists to answer biological questions that weren’t answerable before because it provides scientists with a new way of observing nature.

The complementary vision of computers is especially prominent in the studies of biological traits, according to Berger-Wolf. Biological traits are the interplay between genes and the environment. They can be physical characteristics such as “beak colors, stripe patterns, fin curvatures, the curves of the belly or the back.” They can also be behavioral characteristics such as possums playing dead or pollen feeding in birds. Being able to observe traits “is the foundation of our understanding of how these traits are inherited and the understanding of genetics,” insights into animal behavior, and ecological and evolutionary theories.

In order for biologists to propose new evolutionary hypotheses to explain biological traits, it is crucial to “make these traits computable.” Starting from a project funded by the National Science Foundation, Berger-Wolf founded Wild Me. This nonprofit organization has an ongoing initiative, Wildbook, that collects images containing animals from numerous sources, including camera traps, drones, and even tourists’ social media posts on YouTube, Instagram, and Flickr.

Those source images serve as a starting point for a branch of research in imageomics, which will allow researchers to develop open software and artificial intelligence for the research community. Those tools would allow biologists to discern biological traits that are too similar or too subtle to their eyes, such as animal coat patterns or species that look alike yet are genomically different. Computer vision would allow scientists to find out whether traits are inheritable or shared by multiple species. Based on those new insights, biologists could then conjure new evolutionary hypotheses and start asking even more interesting questions, to which only imageomics can provide the answers.

Berger-Wolf jokes that she has “multiple research personality,” with a passion for bringing her diverse backgrounds together. By helping to found the new Imageomics Institute, her interests were able to converge. Participating in both worlds—natural and technical—allows her to see “the better way” of working and increasing effectiveness.

She commented that starting conversations between fields increases “mutual respect and understanding of each other’s questions and where we can come together.” Berger-Wolf sums up her career by describing her work as “creating tools that expand our ability to look at more things more carefully and even be able to ask questions that people have never been able to ask before.”

Berger-Wolf is currently working on several projects. One looks at animal coat patterns and correlates them with genetics, heritability, and the overall scientific structure of why some traits are inheritable and others are not. By using imageomics, we are able to understand at a deeper level since humans cannot pay attention to every detail. In another project, she is working on species-level traits of butterflies that mimic other species. Computer algorithms can identify what is similar and different in their appearances, down to the small details. Computers can extract complex information and people can start asking different questions using information normally beyond the scope of human perception.

Berger-Wolf’s recent award for the new Imageomics Institute under the NSF Harnessing the Data Revolution program is extending this work and bringing it to a wider audience. The images to be used as sources come from existing research projects, citizen scientists, organizations like iNaturalist, eBird, and Wild Me, as well as the digitization of the natural history museum collections through the iDigBio project.

There are various opportunities for students at any level and researchers from all over the world to participate in the field of imageomics. Berger-Wolf emphasized that the goal is to have people understand what imageomics is and how it’s significant so that it can be accessible to all.

“It’s not just an opportunity to advance science, but also to engage people in science,” she explains. Her team is built up of multiple researchers and students, sharing a goal of building a community around it. More direct community engagement, outreach events, and conferences are great ways for informing people about imageomics and how people can change the way traits are seen.

“We have incredible privilege to do science. To spend time answering scientific questions that are interesting to us while the public is paying us to do so. It’s important to tell the science to the public, communicate why, and what science brings to the world.”

Get Involved

New community-building activities facilitated by the Midwest Big Data Innovation Hub are continuing throughout 2022. Contact the Hub if you’re interested in participating, or are aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Accelerating Data-Driven Materials Discovery at the Molecule Maker Lab Institute

By Qining Wang

Cancer scientist loading tubes into a lab machine. Photo by the National Cancer Institute.
Photo by the National Cancer Institute via Unsplash

Despite being a fundamental process for innovations in chemistry, biology, pharmaceuticals, materials science, etc., molecular discovery can be a time-consuming and labor-intensive endeavor. The traditional trial-and-error approach through experimentation does not always yield promising results. According to a Chemical Abstract Service (CAS) Registry analysis, scientists predict the number of stable light- and moderate-weight organic molecules to be more than 10180. Among those, only 1020 to 1060 are biologically relevant. That’s a lot of molecules, to say the least, let alone discovering the ones that we can use. In the meantime, hundreds of years of research hunting for molecules has yielded an array of successes and failures that we can harvest for data-driven molecule discovery.

To that end, the Molecule Maker Lab Institute (MMLI) and many other AI Institutes funded by the National Science Foundation (NSF) (highlighted in the map below) decided to take this data-driven approach to find the needles in haystacks of molecules quickly and accurately.

Map of NSF-funded AI institutes across the United States.
NSF-funded AI Institutes across the United States

MMLI is a partnership between the University of Illinois at Urbana-Champaign, Pennsylvania State University, and Rochester Institute of Technology. The institute fosters extensive collaborations among artificial intelligence (AI) and chemical and biological syntheses. Those collaborations serve to develop frontier AI tools and dynamic open-access databases. Current research at MMLI involves both small molecule discoveries and manufacturing.

For molecule discoveries, the Institute is currently focusing on improving the performance of organic solar cells. Compared to silicon-based solar cells, the state-of-the-art materials for solar energy harvesting, organic solar cells, are more flexible. They can also be manufactured at large scales at relatively low prices.

However, certain caveats prevent organic solar cells from replacing silicon-based solar cells. Unlike silicon, organic molecules are less efficient at converting solar power into other forms of energy like electricity. Those molecules cannot endure sunlight irradiation for a long time. (Think of pigments on your outdoor furniture that gradually fade away under sunlight. That is sunlight irradiation degrading organic molecules on display.)

To overcome these challenges, MMLI is currently developing AI-enabled tools such as AlphaSynthesis to accelerate the discovery of long-lasting and more efficient organic molecules for sunlight harvesting. Guided by machine-learning models, the team led by Martin Burke is able to screen through potential candidates at high throughput. “The team has an ambitious ‘10-10’ target to create organic photovoltaics with a greater than 10% efficiency and a 10-year lifetime,” said Celine Young, Managing Director of MMLI. “Led by a team of experts in AI, automated chemical synthesis, and automated additive manufacturing, the MMLI is employing a closed design-build-test-learn loop to work towards this goal.”

In terms of chemical manufacturing, MMLI primarily focuses on catalyst discovery. Catalysts are a crucial component for efficient chemical production, as they lower the energy barriers of chemical reactions. A catalyst is a local guide who can always tell you the fastest route to a specific destination. Without an efficient catalyst, commercializing any chemicals beyond lab-scale syntheses would be a great challenge.

To find the best catalysts for certain chemical transformations, MMLI developed new AI algorithms to find catalysts that can assist in making the desired molecules. Currently, the team led by Scott Denmark is using AI-enabled tools in hard-to-find catalysts for carbon-hydrogen (C-H) bond oxidation reactions. These reactions can change the properties of a molecule. In C-H bond oxidation reactions, a catalyst breaks the C-H bonds in the molecule and facilitates the formation of new chemical bonds like carbon-oxygen (C-O) bonds. Those reactions are crucial in drug synthesis and converting feedstock chemicals into higher-value chemicals.

MMLI not only stands at the forefront of innovations in AI-based molecule syntheses, but the Institute also realizes the barriers entering the field of molecule synthesis and manufacturing. Broadly speaking, the field is only accessible to a handful of experienced specialists with years of training. To break down such barriers, MMLI created Thrust 5, which aims to train junior scientists, engineers, educators, and practitioners on advanced chemical synthesis and AI skills. They deliver “MMLI in a Box” to classrooms in the USA and launch the Molecule Maker Digital Learning Platform to expose K–12 students to molecule making early on in their education.

Get Involved

MMLI is currently seeking applicants for their MMLI Seed Grant Program. Find out more about this opportunity and submit your grant proposal here by April 30, 2022. The Institute is also seeking industry partners that foster knowledge sharing between the MMLI and industry researchers.

The Midwest Big Data Innovation Hub will be doing a community data needs assessment in the advanced materials space later this year to understand key challenges around materials data management. Contact us if you’re interested in participating, or if you’re aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Student Group Profile: DREAM at Minnesota State University, Mankato

The Midwest Big Data Innovation Hub is developing a community of data science student groups across the Midwest region to share their experiences and best practices. This story is part of a series of student group profiles.

For this profile, we spoke with leaders from DREAM, Data Resources for Eager & Analytical Minds, a recognized student organization at Minnesota State University, Mankato. It has over 300 student members who focus on data science, data analytics, machine learning, artificial intelligence, information technology, and computer science. DREAM organizes and hosts conferences, trainings, competitions, and industry talks to support the students’ academic and professional development. The DREAM members have won many awards at various data science competitions and have authored dozens of research papers and conference presentations. DREAM is a past recipient of the Outstanding RSO of the Year award.

Minnesota State University, Mankato DREAM logo

What are the goals of your group, and who is your core audience?
DREAM was founded in 2016 when one dedicated data science professor at Minnesota State University, Mankato (MNSU), Dr. Rajeev Bukralia—the esteemed faculty advisor of DREAM—excited the students of the potential of and career opportunities in data science. Since the start, DREAM’s goal has been to explore, raise interest in, and share the wonders of data science and related fields. Our mission is to help students venture into the more interesting aspects of data science and corresponding fields, and in the process, connect students to industry mentors and professionals. We want to support anyone from any background who has interest in data analytics, data science, or computer science. Our core audience is varied because data itself is varied and can come from any field. Our audience is anyone who wants to understand that data on a deeper level, be they business majors, biology students, or just about anything else; we welcome anyone from any background who wants to participate!

What kinds of activities have you done previously, and what do you have planned for this year?
COVID has changed the format of our group considerably, but we still have regular industry talks and we act as a center for communicating events and opportunities to students interested in data science. Recently, we have had multiple industry leaders speak on their experiences working in the industry. They shared their experiences and tips to help set students up for success. So far this semester, we have hosted four industry talks with professionals from big companies such as UnitedHealth, One Drop, and Ovative. The larger projects we have planned for this semester focus around supporting students through the 2022 Data Derby Hackathon, setting up the spring election, and creating fun, themed training sessions for students to dip their toes into key tools for data science, such as Python and Power BI. We also hope to involve the members of our club in a student research showcase this spring in collaboration with MinneAnalytics.

As DREAM grows, we hope to expand our reach into the community. Through school or library programs, we hope to spark an interest in data science in kids grades 6 through 12. Programs like this would not only have to be volunteer-run, but also volunteer-created. So, after completing a few training sessions at the university, we hope to create an introductory data science curriculum that is interesting enough to captivate young students, but also approachable enough for young students.

What challenges have you faced in starting or maintaining your group?
The pandemic, of course, has been a large shift for a group like ours, which has over 300 students, dozens of which would be packed into a room eating pizza together on any given Thursday night pre-COVID. Since then, we have had to switch to Zoom for our meetings, although we’re trying to get back in person soon. There are also the general challenges of collaborating with university administration to secure and maintain the backend functions of the club and making sure to bring in a constant stream of new students to sustain the club.

What suggestions do you have for others who want to start a group on their campus, or expand their current group?
Reach out and promote your group through classes on your campus that are relevant—for example, we promote DREAM in the introductory data science courses and the database management courses.

Run events regularly—consistency will help build up more engagement, both from members of the group that are excited to participate more, or from members of the student body that just decide to pop into one meeting because they see it happening every week.

Keep a careful eye on your roster. Make sure you always have a copy backed up. Also, keep it organized so you can keep track of current students, alumni, etc. Your email roster is your direct point of contact with your group, so be sure to communicate with them regularly and to always maintain the current contact details.

Stay true to the mission. Be active and involved in community events. Try different methods to promote your group’s spirit and resources, such as Twitter and LinkedIn, etc.

Get involved

You can find the DREAM club on Twitter and their website.

Are you a student group leader or advisor? We’d like to hear more about your group’s activities. Contact us if you’d like us to profile your organization or participate in our student groups webinar series. You can also join our new Slack community to continue the discussion and make new connections.

About the Midwest Big Data Innovation Hub

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

University of Nebraska researchers extend smart rural bridge health initiatives

By Raleigh Butler

Did you know that, despite increases in technology, bridge health across the United States is decreasing? Bridges currently score a C on the country’s infrastructure report card, which is a fall from last year’s grade.

Within the Midwest, the percentage of structurally deficient bridges per state include the following:

  • • Iowa has the largest percentage, 19.0%.
  • • Minnesota has the smallest percentage, 4.7%.

The Midwest Big Data Innovation Hub’s Smart & Resilient Communities priority area spans a range of disciplines, sectors, data, and cyberinfrastructure in its work to connect researchers and practitioners focused on community resilience. Bridges play key roles in community planning, resilient supply chains for food and goods, and in transportation capacity management.

Foundations

In 2018, a new regional innovation center project, “Smart Big Data Pipeline for Aging Rural Bridge Transportation Infrastructure (SMARTI),” was funded by a $1 million National Science Foundation (NSF) grant. The grant was aimed toward “rural bridge health management” and included faculty from both the University of Nebraska–Lincoln (UNL) and University of Nebraska Omaha (UNO). The work began with a planning grant in 2016, and both awards were part of the NSF’s Big Data Spoke program, in collaboration with the regional Big Data Innovation Hub program.

The principal investigator for the project, Robin Gandhi, is from UNO’s College of Information Science and Technology. The 16 research team members also include Daniel Linzell and Chungwook Sim, both from UNL’s College of Engineering.

The SMARTI project focused on “mining existing data sets from private, state and federal partners, as well as collect[ing] new data through sensors on targeted rural bridges throughout Nebraska.” The outputs of this work were presented through workshops and made available to researchers through the Bridging Big Data website.

“Our government and industry partners can better manage their aging rural bridges, improve their health and ultimately keep people safe using data and tools developed from our research,” said Robin Gandhi. “We continue to engage stakeholders through companion research projects and by presenting our work at relevant technical meetings and conferences. For example, we will be presenting at the Midwest Bridge Preservation Partnership, the American Society of Civil Engineers Structures Congress in April, and the International Association for Bridge Management and Safety Conference in July 2022.”

Student engagement

Six students from both the Lincoln and Omaha campuses who are working on these projects presented their research in October 2021 at the Midwest Big Data Innovation Hub’s Regional Community Meeting, with a focus on the data sets and data science tools that are important to this work. Recordings of their presentations are available on the MBDH YouTube channel.

Next steps

Approximately three years after the start of the SMARTI project, the Nebraska team was awarded $5 million by the Department of Defense Army Corps of Engineers for research to extend the lifespan of bridges through new monitoring technology. This award was announced in October 2021.

The researchers will continue with their work on bridge safety. The team will use rural Nebraska as testbeds for locations to safely collect data, as well as to analyze “socio-technical impacts such as fairness of data, algorithms, and analysis; and intelligent decision-making and support systems.”

“This project brings bridge owners, designers, and builders, big data solution providers, and academics together to discuss data-informed bridge infrastructure health and resilience in times of crisis,” said Daniel Linzell. “Attendees at our last workshop heard from several stakeholders about the pandemic’s impact on bridge infrastructure resilience from design, sensing, economic, and socio-political perspectives. Discussions such as these keep the research team focused on the importance of the work: developing sensing and big data technology applications that support smart, resilient, big data pipelines for aging rural bridge transportation infrastructure; highlighting solutions to data discovery and controlled sharing challenges; and unveiling novel data-driven decision-making tools.”

Get involved

New activities to build the community of Midwest researchers and practitioners in the Smart & Resilient Communities priority area of the Midwest Big Data Innovation Hub are beginning in spring 2022. Contact the Midwest Big Data Innovation Hub if you’re interested in participating, or aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Water Data Forum Webinar Series

Header for the Water Data Forum web series presented by the Cleveland Water Alliance, Water Environment Federation, and Midwest Big Data Innovation Hub.

Water Data Forum, the virtual series presented by the Cleveland Water Alliance, Water Environment Federation, and Midwest Big Data Innovation Hub, is returning for a second season in 2022!
In 2021, the Forum assembled expert panels to engage in timely topics such as new sensor and control technologies as well as water data for environmental justice and climate resilience. This year, interactive web sessions will engage a diverse array of experts across sectors in an exploration of topics ranging from the intersection of cyber security and water to STEM and youth empowerment.

2022 Sessions

The new season will kick off this March with a session titled: Innovations in Water Quality: The Real-Time Revolution on March 30 at 12 p.m. ET. This session will convene industry, government, and research experts to explore the next generation of water quality sensing technologies. In a facilitated discussion, panelists will use specific case studies to examine the challenges posed by new, or more recently understood, sources of water pollution and the opportunities surrounding real-time networks and new sensing modalities.



May Session: Cyber and Water: Driving Digital Security across the Water Sector
July Session: Smart Stormwater: Data-Driven Response to Flooding, Erosion and other Natural Hazards
September Session: Water Education: STEM, Youth Empowerment and Workforce Development
November Session: Smart Water Equity: Data-Enabled Affordability, Justice and Sovereignty

Robust, accurate data are crucial for the future of water resource management, economic and workforce development, and technological advancement. Water Data Forum aims to demystify the complexities of water data for seasoned experts as well as the general public. For more information and updates around speakers and registration, visit https://clevelandwateralliance.org/wdf.

Get involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas, which include Water Quality. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Student Group Profile: Girls Who Code, University of Michigan DCMB

The Midwest Big Data Innovation Hub is developing a community of data science student groups across the Midwest region to share their experiences and best practices. This story is part of a series of student group profiles.

University of Michigan Girls Who Code logo

In light of Women’s History Month and International Women’s Day on March 8th, we talked with the leaders of Girls Who Code club at the University of Michigan about their work on empowering young girls to participate in coding projects and the STEM field by and large.

What are the goals of your group, and who is your core audience?
We are an organization founded by doctoral students from the Department of Computational Medicine and Bioinformatics at the University of Michigan. Our goal is to provide a collaborative and supportive environment for students of all skill levels and backgrounds interested in learning to code. Our club curriculum focuses on computational data analysis and the Python programming language. Participants learn fundamental coding concepts and implement their new skills in their chosen data science capstone project. Our core audience includes girls, women, and allies who support our mission of closing the gender gap in technology.

What kinds of activities have you done previously, and what do you have planned for this year?
Our Girls Who Code club meets weekly from September through May. During the summer, we offer a two-week intensive Summer Experience (SE) program. During club and SE, students participate in live coding lectures, work through paired programming exercises, hear from guest speakers, and complete a data science capstone project. We have also facilitated field trips to the Ann Arbor Google office and connect students to faculty at the University of Michigan for long-term research experiences. Along the way, we have partnered with other STEM outreach organizations at the University of Michigan. For instance, this year, we will collaborate with FEMMES (Women+ Excelling More in Math, Engineering, and the Sciences) and DFB (Developing Future Biologists) to provide hands-on programming activities.

University of Michigan Girls Who Code group photo

What challenges have you faced in starting or maintaining your group?
A primary challenge we faced in starting the club and SE programs was the lack of live-coded Python for data science curriculum for our target age group (high school). However, given the expertise of our student facilitators, we were able to develop a custom curriculum teaching Python fundamentals and data science skills, including statistical analysis, from scratch. We rely entirely on hard-working undergraduate, graduate, and postdoctoral volunteers, and recruiting volunteers who can dedicate time to this extracurricular activity is often difficult. To help address this challenge, we have started paying our SE instructors. The pandemic created a massive shift in how we delivered our programming, and we had to shift the club to a virtual format within a week. We have continued virtual instruction, and despite its challenges, we have been able to expand our reach.

University of Michigan Girls Who Code Zoom screenshot 1
University of Michigan Girls Who Code Zoom screenshot 2

What suggestions do you have for others who want to start a group on their campus, or expand their current group?
Find ways to collaborate with existing organizations so that you can build on their previous work instead of reinventing the wheel. Identify and understand the needs of the communities that you’re interested in working with to ensure that your programming aligns with your target audience. It’s also a good idea to consider your organization’s longevity and plan at the onset for the transfer of leadership responsibilities after the original leadership moves on. Creating documents that allow for knowledge transfer and working with faculty that can provide continuity are two such ways to address this.

Get involved

You can find the Girls Who Code club on Twitter, Facebook, and their website. The club has also compiled resources on coding, online teaching, and fostering diversity, equity, and inclusion on their GitHub page.

Are you a student group leader or advisor? We’d like to hear more about your group’s activities. Contact us if you’d like us to profile your organization or participate in our student groups webinar series. You can also join our new Slack community to continue the discussion and make new connections.

About the Midwest Big Data Innovation Hub

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Student Group Profile: Iowa State University Data Science Club

The Midwest Big Data Innovation Hub is developing a community of data science student groups across the Midwest region to share their experiences and best practices. This story is part of a series of student group profiles.

For this profile, we talked with leaders of the Iowa State University Data Science Club.

Iowa State University Data Science Club logo

What are the goals of your group, and who is your core audience?
Our main goal is to promote the field of Data Science, whether it be information on the field, internship opportunities, school resources, or skills you need to learn to get a job in the field.

Our main audience is data science majors and any other adjacent majors with some prior coding experience. And anyone, in general, that would be interested in this type of career.

What kinds of activities have you done previously, and what do you have planned for this year?
We have focused a lot on company presentations and internship opportunities in the field. We have now been focusing on workshops surrounding data science essentials, like Google Cloud, Machine Learning, or Tableau basics.

What challenges have you faced in starting or maintaining your group?
One of the main challenges has been keeping people engaged. Workshops aren’t super fun but essential to learning about the field. Company presentations are nice but don’t appeal strongly to freshmen and sophomores. We have been working on making the club more of a community. Having members help each other with homework, talk about outside activities, have fun events occasionally that don’t relate to data science, but just make a place for collaboration and talk to others about their love for the field.

What suggestions do you have for others who want to start a group on their campus, or expand their current group?
Start big, expect small. In the beginning, focus on appealing to as many as possible. Do as many things as you can to interest people. But always have a foundation for your goal as a group, stay centered, stay consistent. You may have a ton of people at the first meeting and very few at the next, but the key is to stay consistent and think big picture.

In terms of expansion, bring outside help, see if your school can help, collaborate with outside companies. Put yourself in a position where your group will not just be a fun place to hang out but a place that could benefit your resume and help bring you to experience for future internship opportunities.

Get involved

Are you a student group leader or advisor? We’d like to hear more about your group’s activities. Contact us if you’d like us to profile your organization or participate in our student groups webinar series. You can also join our new Slack community to continue the discussion and make new connections.

About the Midwest Big Data Innovation Hub

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

MBDH Learning Innovation Fellows Program Builds on Success with Second Cohort

The Midwest Big Data Innovation Hub and the Gala Sustainability Learning Initiative at the University of Michigan School for Environment and Sustainability continue to build on the success of last year’s Learning Innovation Fellows pilot program with a second cohort of fellows. The student fellows, hailing from a range of midwestern institutions, work with faculty advisors at the intersections of the Midwest Hub’s “Cyberinfrastructure and Data Sharing” and “Data Science Education and Workforce Development” themes. The program brings together data science and sustainability, delivering open-access, data-enriched learning tools on the Gala platform, along with experiences and mentoring for student fellows.

Teams

Alternative Transportation Scenarios
Shanshan (Shirley) Liu

Shanshan (Shirley) Liu (Student Fellow) is a PhD student from the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. Her research interests include transportation electrification policy and planning, sustainable transportation systems, and transportation energy. Shirley’s project is based around Shelie Miller’s case study, Assembling Our Transportation Future, which asks readers to think about transportation policy hinge points in American history. She is using Python to create tools that allow students to analyze scenarios of alternative vehicle adoption and evaluate them from the perspective of energy consumption and carbon emissions.

Shelie Miller

Shelie Miller (Faculty Advisor) is a professor at the University of Michigan School for Environment and Sustainability. Her research uses life-cycle assessment and scenario modeling to identify environmental problems before they occur. Miller’s research group works on a variety of energy-related topics, including the energy-water nexus, bioenergy, refrigeration in the food system, and autonomous vehicles.





Modeling Rainforest Carbon Cycling
Anneke van Oosterom

Anneke van Oosterom (Student Fellow) is a sophomore double majoring in biology and data science at St. Catherine University. She is currently involved with the biology department at St. Kate’s through the Biology Club and as a microbiology lab prep assistant. Through the fellowship she is creating a systems model using the Insight Maker modeling tool to demonstrate carbon cycling in tropical rainforests for Ann Russell’s forthcoming case Healing the Scars: Tropical Rainforest Carbon Cycling (developed through the OCELOTS network for tropical ecology).

Ann Russell

Ann Russell (Faculty Advisor) is a terrestrial ecosystems ecologist at Iowa State University, with special expertise in the biogeochemistry of tropical and managed ecosystems. Her research addresses links between traits of plant species and ecosystem processes, focusing on species and management effects on belowground processes, and subsequent implications for human impacts on soil fertility and carbon sequestration. Her research is designed to enhance our understanding of human impacts on the biosphere, improve biogeochemical models, and help guide selection of species for sustainable management of agroecosystems.


Scenario Planning for the Rouge River
Julie Arbit

Julie Arbit (Student Fellow) is in her final semester as an environmental policy and planning student within the School for Environment and Sustainability at the University of Michigan (UM). She works as a research associate for the Center for Social Solutions at UM, where her main project focuses on equity in flood risk, response, and recovery. Julie is using ArcGis Online and Python to create scenario planning tools for the case The Rouge River: Redlining, Riverbanks, and Restoration in Metro Detroit.


Perrin Selcer

Perrin Selcer (Faculty Advisor) is an associate professor and director of undergraduate studies at the University of Michigan Department of History. He works at the intersection of environmental history, history of science, and international relations.







Accessible Data Science Tools for Water Utilities
Thien Nguyen

Thien Nguyen (Student Fellow) is a second-year computer science undergraduate and sustainability enthusiast at the University of Minnesota, Twin Cities (UMN). He has previously worked with UMN’s Institute on the Environment, writing geospatial analysis algorithms in Google Earth Engine to observe soil degradation in Senegal’s Peanut Basin. Thien is working with PhD student Matt Vedrin to create tools for a PIT-UN funded collaboration working to help classrooms, communities, and workforces confront challenges in the monitoring and improvement of drinking water distribution systems.

Lutgarde Raskin

Lutgarde Raskin (Faculty Advisor) is a professor at the University of Michigan School for Civil & Environmental Engineering. She works to rethink engineered systems to better harness the power of microorganisms to treat water and recover resources from waste streams. Dr. Raskin and her team work to understand and improve various aspects of the engineered water cycle microbiome to improve human health using sustainable design approaches, with a focus on biofiltration, disinfection, distribution, and building plumbing biostability.



Get involved

This work was supported by the National Science Foundation through the MBDH Community Development and Engagement (CDE) Program.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Professor Kimberly Zarecor on Community-Based Research and Building Interdisciplinary Research Teams

By Qining Wang

An expert in Eastern European Architecture, Professor Kimberly Zarecor tells us about her journey of building a highly interdisciplinary research team that takes data science into research on rural communities in Iowa.

Kimberly Zarecor

To some, architectural history and data science research may sound like oil and water—two fields that are almost impossible to mix well. However, Kimberly Zarecor, professor of Architecture at Iowa State University (ISU), leads her research team to create the perfect emulsion of many seemingly unrelated fields: sociology, statistics, industrial design, data science, architecture, and beyond.

With a research focus on small and shrinking communities in rural Iowa, not only does the team uncover the community efforts that keep some of these towns thriving, but the team is also offering the broader research community a valuable lesson on how to bring a wide range of expertise to projects and how experts from different fields can work together in harmony.

Zarecor found her inspiration to study Iowa’s shrinking towns from Ostrava, in the Czech Republic, a city she studied during her PhD research and later lived in for a semester as a Fulbright scholar. “[Ostrava] was part of a study in Europe called the Shrink Smart project, where [researchers] were looking at Ostrava as a shrinking post-industrial European city and questioned how to manage the governance of a relatively large city in the context of population loss.” As Zarecor shifted her primary research focus from architectural history in Eastern European cities to rural population loss in the Midwest, she realized the concept of shrinking smart could also be applied.

Zarecor and her collaborators started exploring the data-science component of shrinking smart with funding from a Smart & Connected Communities planning grant from the National Science Foundation (NSF) in 2017. Researchers at Iowa State University have been collecting data about the quality of life in small Iowa towns through the Iowa Small Town Poll since 1994, but “nobody had ever brought a data-science mindset to the analysis of [this] data.” The sociologists who had been collecting the data did not “think of [the poll] as a large set” and had not thought to build “a predictive model” from it.

Zarecor invited a computer scientist to be part of the planning grant team to transform the Small Town Poll data into training data, from which they could construct models to understand and predict the factors that influence people’s perceptions of quality of life in small rural communities. “We realized that what we were trying to understand is what are the actions that people in communities take as inputs into a system that results as outputs on the other side, as increases in perceptions of quality of life,” Zarecor explained. The planning grant team, consisting of a computer scientist, a sociologist, a community and regional planner, and two architects, found that “the best way to define [rural smart shrinkage] is that you are actively pursuing specific activities that you as a community can do together” that contribute to improved perceptions of quality of life even as population loss continues.

In 2020, Zarecor received another NSF grant of $1.5 million to continue this research and investigate strategies to address the data deficit in shrinking rural communities.

As the scope of the research expanded, so has Zarecor’s team. In addition to Zarecor and rural sociologist David Peters, who was also a Co-PI on the planning grant, the team now includes a community economic development specialist and a community arts specialist from ISU Extension and Outreach (both are also faculty in the College of Design at Iowa State), an industrial design faculty member, masters students from industrial design and community and regional planning, and for the data science work, three statistics faculty and three statistics PhD students. The Iowa League of Cities is also a partner on the project.

Coming to data science with little technical understanding, Zarecor approaches the data science component more from an intuitive rather than conceptual perspective: “It’s not that I understand the statistics, but I understand [the goals] as we go step by step . . . [and] the power of the tools that [the statisticians] are building.”

To lead such a highly interdisciplinary team, Zarecor thinks of herself as a bridge-builder within the team. Zarecor helps the members of her team understand data science by asking questions in a way that they can elicit responses that deepen the understandings of the nontechnical team members. “I like having that [bridge] function because it’s asking questions as a way of learning. For me, just the conversations with the data scientists helped me to better understand the data science part of our project.”

And the bridge function goes both ways. In addition to helping non-data-science experts learn more about the potential of data science, Zarecor also cultivates data scientists’ ability to contribute to projects that are community-based. “When it comes to community-based work, the assumption that this is not an expertise of its own is something that’s a challenge for the field, because doing work in communities is its own expertise,” Zarecor explained. Even though the residents in rural Iowa are the direct beneficiaries of the work from Zarecor’s team, the knowledge gap with respect to finding and using data makes those benefits inaccessible to some residents. Meanwhile, data scientists often lack the skills to convey their findings to an audience outside their academic circle. “As a field, data science, in my opinion, has not done a good job to educate necessarily well-rounded [data scientists].”

To overcome this bottleneck, Zarecor’s team works on creating dashboards that visualize the data and make the data more interpretable to the rural communities. Zarecor also encourages the statisticians on her team to talk to residents of the communities they study and ask what kind of data they would like to have. “When we ask what they want, it’s not because they know everything that’s available. We’re doing a mix of hearing from them what they want, and also guessing some things that they probably don’t know are out there that we can also give them in a usable form.”

Zarecor believes that similar types of highly collaborative and interdisciplinary research would benefit the entire research community, and those collaborations start with abandoning assumptions of different fields.

She gives an example in the discipline of architecture, where architects would assume themselves to be capable of doing graphic design or planning. Many don’t realize that those tasks are outside of their expertise even though these fields are seemingly adjacent. “And I would transfer that over to data scientists who know that data science is a synthetic and integrative discipline. [. . .] It doesn’t mean, though, that there are not all of these soft skills, all of this other communication, and people-related aspects of the data science work that you can handle without help.”

Therefore, Zarecor suggests that data scientists should work in conjunction with domain experts to make their research more relatable to a broader audience. Team members also need to respect the importance and specificity of other kinds of expertise beyond the technical or data-driven parts of a project. When a team successfully works this way, “the data science gets improved and amplified and becomes more useful. If you actually think horizontally on the project, you know that there’s not a pyramid, but that you are a team that’s working across the group [of collaborators]. This would be a much healthier way of [working with] data and for data scientists to interact with people.”

In this regard, Zarecor noted that the Midwest Big Data Innovation Hub, as a highly integrated and inclusive organization, has the potential to cultivate different layers of collaboration across various disciplines. “But it does require the data scientists who were the first audience, or the more explicit audience [for the Hub], to be willing to open up.”

Get Involved

New community-building activities in the Smart & Resilient Communities priority area of the Midwest Big Data Innovation Hub are beginning in spring 2022. Contact the Hub if you’re interested in participating, or are aware of other people or projects we should profile here. The MBDH has a variety of ways to get involved with our community and activities

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

New MBDH Community Development and Engagement partners

By Qining Wang

The Midwest Big Data Innovation Hub (MBDH) recently partnered with multiple institutions in the region for new data science activities under its Community Development and Engagement Program. This program incubates new projects and provides support to help them grow.

In the last proposal cycle, the MBDH Seed Fund Steering Committee selected three projects to support, led by the Tribal Nations Research Group (TNRG), St. Catherine University, and Trinity Christian College.

TNRG Digital Agriculture Meeting

The TNRG, together with the University of North Dakota and Grand Farm/Emerging Prairie, will host a one-day workshop in 2022, at the Microsoft Business Center in Fargo, North Dakota. This workshop will connect tribal colleges and universities working with their local tribal governments to extend digital agriculture and educational opportunities to Native farmers.

Approximately 30% of the nation’s Native population and 20 of the 37 of the nation’s tribal colleges and universities are located in the MBDH service area. Because of this, the MBDH is well-positioned to engage tribal stakeholders on issues related to Data Science Education and Workforce Development. This is especially true in the context of Digital Agriculture, where many of these institutions are working with their local tribal governments to extend agricultural programs and educational opportunities to Native farmers.

Tribal communities have not had the dedicated capital for building a resilient and sustainable infrastructure for harnessing food on their lands for a long time. The lack of such infrastructure creates food insecurity that can be detrimental to Indigenous peoples. In addition, due to climate change, it is crucial to build sustainable farming practices that can provide sufficient food and preserve the ecosystem everywhere in the long run.

One way to realize optimal farming practices is to incorporate digital agriculture, which integrates digital technologies into crops and livestock management. Technologies such as machine learning and big data analysis tools can improve agricultural production while minimizing the harm to the ecosystem. For instance, by correlating multiple parameters related to crop growth using machine learning, farmers can better predict crop yield based on other parameters such as nutrients in the soil, weather, and fertilization. Those technologies can therefore make information on ecosystems, crops, and animals more findable and interpretable to farmers.

However, implementing digital agriculture on tribal lands involves extra layers of nuance. Data scientists and agricultural experts must conduct digital agriculture research in tribal regions under proper data sovereignty standards, such as the CARE Principles for Indigenous Data Governance. Indigenous peoples are entitled to know what data is collected and how data scientists use and analyze their data. The data should enable Indigenous peoples to derive benefit from any fruits of the research involving tribal communities.

This workshop will serve to increase the accessibility of digital agriculture in Native communities, emphasizing respecting the culture, traditions, and sovereignty of the Native people. In addition, this workshop will enlist more tribal stakeholders nationwide for broader engagement in digital agriculture, potentially developing a Data Science Workforce Development and Education proposal for Native communities. Anita Frederick, the President of TNRG, will lead this workshop and present the importance of Data Management and Data Sovereignty.

“Outreach to Indian tribes is often difficult for non-tribal entities and individuals,” Frederick said. “As a direct result, tribal populations are often left out of initiatives that could help to address some of the economic, health, and other societal conditions that tribes face. Clearly, American Indian citizens must have access to the opportunities envisioned in the Big Data Revolution. The proposed project is a first step in helping to close the growing Big Data gap that is emerging between Indian country and the rest of the nation.”

St. Catherine Data Science Boot Camp

MBDH will also support a data science program “created by women for women” at St. Catherine University (aka St. Kate’s), one of the USA’s largest private women’s universities, located in St. Paul, Minnesota. This program aims to cultivate a new generation of women and historically underrepresented data scientists. In addition to teaching data science and data analytic principles, this program will also raise students’ awareness of using data science in ethically, socially, and environmentally just ways.

Introduced in the fall semester of 2018, the data science program at St. Kate’s reaches both current and prospective students of the University. Monica Brown, the Mary T. Hill Director of Data Science at St. Kate’s, will lead the program’s two initiatives in 2021-2022. Working alongside her colleagues at St. Kate’s for over 13 years, Brown aspires to make data science and data analytics principles accessible to every student in the St. Kate’s community.

Brown will launch a one-week Data Science Boot Camp in the summer of 2022. This boot camp will provide hands-on coding experience to middle- and high-school students, particularly those historically excluded from data science. In addition, Brown will invite data science professionals to speak about future career opportunities. Overall, this program aims to enable younger students to envision themselves as future data scientists and to elicit their passion for coding and data science. The lessons learned organizing this event will be shared with others who wish to do so with their own student populations.

“St. Kate’s is grateful for the partnership with MBDH towards the support of a boot camp,” said Brown. “We very much look forward to bringing younger students onto our campus to encourage and empower them through data science activities.”

Trinity Data Science for Social Good Workshop

The third project to be incubated under the MBDH’s Community Development and Engagement program will be an annual workshop and conference on Teaching with Data for Social Good (DSG) in summer 2022. DSG addresses the importance of teaching data science for positive social impact, and this conference serves as an opportunity that encourages teaching faculty to include DSG in their curricula proactively.

Trinity Christian College, a faith-based institution located on the outskirts of Chicago, will host this meeting. The workshop chair will be Dr. Karl Schmitt, an assistant professor in the Data Analytics department at Trinity and the coordinator of the Data Analytics program.

The meeting format resembles that of regional professional society meetings, consisting of a workshop, keynotes, and contributed talks. To provide more practical assistance to teaching faculty incorporating DSG, faculty will directly generate teaching materials that include DSG in the primary workshop sessions. Additionally, faculty will also have a chance to practice teaching DSG by actively advising student teams participating in a colocated datathon. In this student competition, student teams will use data science to solve practical problems.

“An important component of increasing persistence and success for our current generation of students is connecting their coursework to meaningful change or outcomes,” Schmitt said. “Through the Workshop on Data for Good in Education, the MBDH will be supporting faculty in developing their teaching to better incorporate the Data for Social Good (DSG) movement. This provides a natural connection to relevance with grass-roots level improvements in our society while promoting the broad applicability of data science.”

Beyond these outcomes, Schmitt said, “the workshop will be a professional development opportunity for all instructors seeking to more deeply engage their students through meaningful social good projects within a classroom setting. It will inspire, educate, and most importantly, allow faculty the chance to share, and prepare, materials for use within their own teaching context.”

Get involved

Learn more about other Community Development and Engagement partnerships, and contact the MBDH if you have an idea for a project to help build the data science community in the Midwest.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Agroterrorism: Cybersecurity Incidents Affect Agriculture and Water

By Raleigh Butler

You may not think that agriculture and cybersecurity, both themes of the Midwest Big Data Innovation Hub, are linked, but recent events demonstrate there are connections between the two that pose risks to our food security.

The “food and agriculture” industry is publicly defined as a critical infrastructure sector by the U.S. Department of Homeland Security. The Cybersecurity & Infrastructure Security Agency (CISA) states that food and agriculture is one of sixteen essential critical infrastructure sectors that provide “the essential services that underpin American society and serve as the backbone of our nation’s economy, security, and health. We know it as the power we use in our homes, the water we drink, the transportation that moves us, and the communication systems we rely on to stay in touch with friends and family.” Those statements highlight the urgency of building robust cyberinfrastructure to prevent massive disruptions to crucial public services.

A recent cyberattack targeting an Iowa-based agriculture company called New Cooperative illustrates the severity and consequences of those incidences. The group claiming responsibility—BlackMatter—deals in blackmail, Reuters reports. The hackers from BlackMatter locked New Cooperative’s access to data that support the food supply chains and detail the feeding schedule of the livestock. In order to get access to the decryption key for its data and reinstate their farming activities, New Cooperative was ordered to pay $5.9 million.

As Bobby J. Martens, an associate professor of Economics at Iowa State University was quoted as saying, “This event wasn’t long enough to cause a change in the commodity price, but certainly it will have ramifications in terms of the food supply system. If they do it to this company, they could do it to one of the majors. They can block the food chain. They attacked in the heartland of all agriculture. It’s a new form of terrorism.”

Regardless of the source, and whether it is purposeful or accidental, a failure in any other critical sector could be life threatening for US citizens. For example, Water and Wastewater Systems is a related sector on CISA’s list, and in fact, water system attacks did occur early in 2020, the most prominent being the Oldsmar, Florida attack of February 16. While the breach nearly allowed a mass poisoning to occur, the mayor viewed the event as a “success.” According to ProPublica, cybersecurity experts view the breach not as a success, but instead as a “frightening near-miss.” Retired Admiral Mark Montgomery, a panelist on the MBDH Water Data Forum webinar on water and cybersecurity in May 2021, was quoted as saying, “Frankly, they got very lucky. They averted a disaster through a lot of good fortune.”

Nontechnical companies are extremely vulnerable to cyberattacks. According to the 2020 state of ransomware report, manufacturing, government, services, and healthcare are among the top sectors prone to cyberattacks. This link leads to this report from a company called BlackFog, a leading company in ransomware protection.

Moving forward, it is possible for businesses and governmental sectors to make cybersecurity an integral part of their practices. Even seemingly trivial data maintenance, such as regularly backing up data in multiple storage devices and encrypting data during transfer, can improve data security in the long run. The key is to operate under the mindset of protecting data and to be more intentional about data protection at any point. The U.S. National Institute of Standards and Technology (NIST) and CISA developed the NIST Cybersecurity Framework, a comprehensive approach to security for critical infrastructure, and there are subsets of that work to support small businesses and other organizations with cybersecurity risks that may not have extensive resources.

On the management level, designated information security officers can build more secure databases and data management systems. The information security officers can also perform routine testing for weaknesses in the existing systems. They could also work with the risk managers to develop preventative measures in case of cyberattacks. Other preventive measures include purchasing cyber insurance.

An additional benefit of developing systems for monitoring and collecting data is the ability to assess the impact of other external events. We previously published a story on how researchers were assessing the spread of COVID-19 by examining the relative levels of the virus in wastewater systems. Since many infrastructure systems, such as agriculture, water, and food, are an interconnected web of dependencies, threats to one can have cascading impacts across others. For academic organizations that manage research data repositories, the MBDH and its partners developed a guidance document on data security for open science, through our Trustworthy Data Working Group.

Get involved

Do you have a cybersecurity success story or case study to share from your organization? Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Climate Change Affecting Crops in Iowa

By Raleigh Butler

In 2010, the University of Minnesota received a grant from the National Science Foundation to study climate change using data-driven methods. The project included Midwest Big Data Innovation Hub co-PI Shashi Shekhar and a team of researchers from across the country. The research led, in part, to explorations of connections between food, energy, water, and climate change.

Because greenhouse gases contribute heavily to climate change, activities that contribute to their release are becoming more divisive with time. There’s no doubt that the food we eat is becoming an increasingly political statement. According to the 2019 Environmental Protection Agency report, agriculture was responsible for 10% of all greenhouse gas emissions, amounting to 650 million metric tons of CO2. A quarter of those emissions (about 2.5% of all greenhouse gas emissions) come from livestock before they are butchered.

The Coupled Model Intercomparison Project 3, a project of the World Climate Research Programme, predicts when the global average temperature will increase by 2°C. The approximately 0.75°C increase in temperature since 1950 has caused a huge increase in natural disasters. This can be seen by an increase in hurricanes, such as Katrina, and the melting of the polar ice caps, among other issues.

According to the graphic from their report, the global average temperature has already increased by about 1°C (1.8°F) relative to preindustrial levels, and will continue rising to as much as 7°C in some regions by the end of the century.

Climate change is the culprit behind many natural disasters, as more than 170 scientific reports covering 190 extreme-weather events found that around two-thirds of extreme-weather events likely originated from, or were exacerbated by, anthropogenic hazards.

How does this apply to the Midwest? Let’s look at Iowa, where over 90% of its land is used for agriculture. In recent years, extreme-weather events have wreaked havoc on crops.

2020: Inland Hurricanes

Farmers and agricultural specialists were worried in August 2020 when portions of Iowa experienced derechos. Pronounced deRAYchos, these are widespread, long-lived thunderstorms mixed with 100–130 mph winds. According to the National Weather Service, a derecho like this was “a roughly once-in-a-decade occurrence” in the Midwest.

These immensely strong storms destroyed crops and decreased crop output for the season in Iowa. According to the power-outage map published by the University of Wisconsin–Madison’s Cooperative Institute for Meteorological Satellite Studies (CIMSS) below, A quarter of the counties in Iowa caught the worst of the storm. All the affected counties were in the central-east portion of the state.

2021: Drought

There were high hopes that 2021 would bring a better crop return. However, when agricultural scouts crossed Iowa in mid August, they found that the state was suffering from extreme drought.

Although derechos and rain-damaged fields were no longer the center of concerns, 2021 has brought high levels of drought. According to the U.S. Drought Monitor, on August 17, 2021, 79% of Iowa was impacted by some degree of drought.

National Drought Mitigation Center map of the 2021 drought in Iowa
The U.S. Drought Monitor is jointly produced by the National Drought Mitigation Center (NDMC) at the University of Nebraska–Lincoln, the United States Department of Agriculture, and the National Oceanic and Atmospheric Administration. Map courtesy of NDMC.

The areas were being scouted out ahead of time for the upcoming 2021 Pro Farmer Crop Tour. Scouts on crop tours have the job of evaluating likely crop production in each region. For more information on crop tours, visit this link.

2021: Storms

Drought became an afterthought just days later. On August 24, 2021, the Midwest experienced multiple storms. Although the severity of the storms did not come close to derechos, they still left behind large paths of downed corn and soybeans. On August 28, 2021, South Dakota and southwest Minnesota even experienced baseball-sized hail.

According to Iowa State University (ISU) Extension Field Agronomist Terry Basol, “The storms hit northeast Iowa farms pretty good, honestly.” Basol said, “It’s amazing the scope of the crop damage,” he continued, concerned about the pace of harvest and crop quality.

Unfortunately, the rain has come too late for many crops, and on top of that, some areas are even flooding. One person, Iowa State University Extension crop specialist Angie Rieck-Hinz, said, “The crop is highly variable. Crop conditions are literally all over the place.”

What’s to Come?

Amidst all these natural disasters and climate change, what can be expected for the future of agriculture in Iowa? In April 2021, the Environmental Defense Fund commissioned KCoe Isom, an agricultural consultancy, to model the potential climate change impacts on Iowa corn, soy, and silage production over the next two decades. According to that site, “Iowa farmers could see statewide gross farm revenues reduced by as much as $4.9 billion per decade. Because with climate change agricultural prices are likely to rise, relative to without climate change, the impact to gross farm revenues from yield impacts will be offset to some degree by higher prices.”

Unfortunately, the increase in climate change (and resulting natural disasters) is likely to continue reducing levels of crop production. This will result in an increase in food prices where those crops are sold, affecting consumers across the country.

The roles for data science and related research around climate and agriculture are growing: in September 2021, the National Science Foundation funded a new multidisciplinary institute led by the University of Illinois, called I-GUIDE, which is focused on better understanding the risks associated with climate change.

Get Involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

How Do Scientists Help AI Cope with a Messy Physical World?

By Qining Wang

When we see a stop sign at an intersection, we won’t mistake it for a yield sign. Our eyes recognize the white “STOP” letters printed on the red hexagon. It doesn’t matter if the sign is under sunlight or streetlight. It doesn’t matter if a tree branch gets in the way or someone puts graffiti and stickers on the sign. In other words, our eyes can perceive objects under different physical conditions.

A stop sign. Photo by Anwaar Ali.
Photo by Anwaar Ali via Unsplash

However, identifying road signs accurately is very different, if not more difficult, for artificial intelligence (AI). Even though, according to Alan Turning, AIs are systems that can “think like humans,” they can still present limitations in mimicking the human mind, depending on how they acquire their intelligence.

One of the potential hurdles is to correctly interpret variations in the physical environment. Such a limitation is commonly referred to as an “adversarial example.”

What Are Adversarial Examples?

Currently, the most common method to train an AI application is machine learning, a type of AI process that helps AI systems learn and improve from experience. Machine learning is like the driving class an AI needs to take before it can hit the road. Yet machine-learning-trained AIs are not immune to adversarial examples.

Circling back to reading the stop sign, an adversarial example could be the stop sign turning into a slightly darker shade of red at night. The machine-learning model captures these tiny color differences that human eyes cannot discern and might interpret the signs as something else. Another adversarial example could be a spam detector that fails to filter a spam email formatted like a normal email.

Just like how unpredictable individual human minds can be, it is also difficult to pinpoint the exact origin of what and why machine learning makes certain predictions. Neither is it a simple task to develop a machine-learning model that comprehends the messiness of a physical world. To improve the safety of self-driving cars and the quality of spam filters, data scientists are continuously tackling the vulnerabilities in the machine-learning processes that help AI applications “see” and “read” better.

What Are Humans Doing to Correct AI’s Mistakes?

To defend against adversarial examples, the most straightforward mechanism is to let machine-learning models analyze existing adversarial examples. For example, to help the AI of a self-driving car to recognize stop signs under different physical circumstances, we could expose the machine-learning model that controls the AI to pictures of stop signs under different lightings or at various distances and angles.

Google’s reCAPTCHA service is an example of such a defense. As an online safety measure, users need to click on images of traffic lights or road signs from a selection of pictures to prove that they are humans. What users might not be aware of is that they are also teaching the machine-learning model what different objects look like under different circumstances at the same time.

Alternatively, data scientists can improve AI by teaching them simulated adversarial examples during the machine-learning process. One way is to implement a Generative Adversarial Network (GAN).

GANs consist of two components: a generator and a discriminator. The generator “translates” a “real” input image from the training set (clean example) into an almost indistinguishable “fake” output image (adversarial example) by introducing random variations to the image. This “fake” image is then fed to the discriminator, where the discriminator tries to tell the modified and unmodified images apart.

The generator and the discriminator are inherently in competition: The generator strives to “fool” the discriminator, while the discriminator attempts to see through all its tricks. This cycle of fooling and being fooled repeats. Both become better at their own designated tasks over time. The cycle continues until the generator outcompetes the discriminator, creating adversarial examples that are indistinguishable to the discriminator. In the end, the generator is kept to defend against different types of real-life adversarial attacks.

AI Risks and Responses

GANs can be valuable tools to tackle adversarial examples in machine learning, but they can also serve malicious purposes. For instance, one other common application of GANs is face generation. This so-called “deepfake” makes it virtually impossible for humans to tell a real face from a GAN-generated face. Deepfakes could result in devastating consequences, such as corporate scams, social media manipulation, identity theft, or disinformation attacks, to name a few.

This shows how, as our physical lives become more and more entangled with our digital presence, we can never neglect the other side of the coin while enjoying the benefits brought to us by technological breakthroughs. Understanding both would serve as a starting point for practicing responsible AI principles and creating policies that enforce data ethics.

Tackling vulnerabilities in machine learning matters, and so does protecting ourselves and the community from the damage that those technologies could cause.

Learn More and Get Involved

Curious whether you can tell a real human face from a GAN-generated face? Check out this website. And keep an eye out for the Smart & Resilient Communities priority area of MBDH, if you wish to learn more about how data scientists use novel data science research to benefit communities in the Midwest. There are also several NSF-funded AI Institutes in the Midwest that are engaged in related research and education.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Teaching During a Pandemic

By Raleigh Butler

This story is part of a series on coronavirus research in the Midwest region. To explore other NSF-funded research addressing the COVID-19 pandemic, please visit the COVID Information Commons, a project of the four NSF Big Data Innovation Hubs.

In early 2020, the USA was brought to a standstill when stores, schools, and other everyday locations closed to help fight the COVID-19 pandemic. This piece will discuss a variety of RAPID awards funded by the National Science Foundation in the Midwest to support research to mitigate a variety of education-related pandemic challenges. Links to the NSF award abstracts will be linked in the article.

Remote Learning Research

A common topic for early school-related COVID-19 research was the exploration of remote or online styles of teaching and learning. In the early stages of the pandemic, it was unclear when schools would be able to reopen. Teachers and administrators were attempting to learn from prior work on remote learning at all levels, kindergarten through college.

For instance, in a project led by researchers from the Chicago Board of Education, researchers discuss the impact of public school students studying computer science remotely. Issues broached include access to the appropriate technology outside of school and possible socioeconomic variables at play. An award to the University of Kansas touches on a similar topic at the graduate level. This work is STEM-focused, addressing COVID-19-related challenges in engineering. One question the researchers ask is: “To what extent do the relationships between perceived e-mentoring support and student outcomes vary by demographics, disciplines, and institutional characteristics?”

A project at the University of Nebraska–Lincoln explores this topic from the faculty perspective. The project goal is described as “to identify cognitive and emotional themes concerning faculty and staff adaptability and community engagement during a crisis compared to those found under typical teaching circumstances.“ Adaptability is a key theme here—professors, regardless of their experience using online-teaching technology, were expected to learn how to do so. In Illinois, the Chicago Public Schools did its own research on forced remote learning and “mitigating the impact” of the sudden transition from in-person to online learning.

Remote Learning Activities

Researchers at the University of Minnesota–Twin Cities put an interesting spin on remote learning with their work on virtual reality (VR). Virtual reality allows learners to immerse themselves in a different world using a pair of electronic goggles or a headset. This device is used to portray a different world, like being “inside” a video game. The Minnesota researchers recognize that “many people, especially young adults, typically being used to active social life, can find this physical/social distancing leading to social isolation. Unfortunately, social isolation is strongly associated with negative outcomes for mental health and therefore represents a serious threat to long-term compliance.” The project aims to promote web-based VR as a way for people to interact safely in a shared environment, despite not actually being physically together.

The need for activities—especially for young learners—is addressed in Indiana University Bloomington’s research project. They have launched a Facebook group called CoBuild19, which works on making STEM activities more accessible to children.

Remote learning has also been addressed in an award granted to the Georgia Research Alliance. This award focuses on “ALOE”—Adult Learning and Online Education. Given the current state of the pandemic, it is immensely difficult, if not impossible, to continue education safely in person. The National AI Institute for Adult Learning and Online Education (AI-ALOE) addresses this by working to move adult-education opportunities online.

Mis/Disinformation

There’s a lot of information available about COVID-19. Some is real, some is misinformation (simply incorrect), and some is disinformation (incorrect with the intent to deceive). Many people have trouble deciding what sources to trust. A project led from the University of Michigan–Ann Arbor plans to follow a sample of university students. The premise of the research is to determine “whether and to what extent people follow recommendations and change behavior.”

Teaching About the Pandemic

Teaching about the pandemic itself is important. A relevant award is an exploration by researchers at the University of Nebraska–Lincoln into using popular media to educate youth on COVID-19-related issues. By using illustrated media such as comics to raise youth awareness of accurate coronavirus-related information, perhaps it’s possible to lessen the mis/disinformation discussed in the University of Michigan’s work. The project proposes assembling “an integrated package of high-quality, widely accessible media and other outreach materials designed to engage middle school youth, educators, and libraries in learning about viruses in relation to COVID-19.”

The researchers, wanting the material to be accessible, propose that “[t]hese resources will be disseminated broadly and at no cost to youth and educators of all kinds, including schools, libraries, museums, and other established networks for formal and informal science education.” Indeed, children’s lives are being altered drastically by COVID-19. It’s important that they know what is occurring to cause such alterations. In fact, the University of Missouri and the University of North Carolina at Chapel Hill collaborated to develop a curriculum for high school students. The curriculum covers epidemics in both scientific and social contexts.

Get involved

The projects described above were all funded by the NSF, which published a related story.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.

Community Engagement through Open Watersheds

By Qining Wang

Lake Michigan and the Chicago skyline. Photo by Muzammil Soorma.
Photo by Muzammil Soorma via Unsplash

Many living in and outside of the USA presume clean water to be universally accessible in the USA. In reality, many people are living in a water crisis.

A recent study published in Nature Communications assesses the degree of the clean water crisis. Researchers found that as of August 18, 2020, more than 22,000 community water systems are either serious violators of or in significant noncompliance with the Safe Drinking Water Act. As the researchers point out, “our findings demonstrate that the problem of water hardship in the United States is hidden, but not rare.”

A huge underlying cause is inaccessible data on water quality. Different governmental and state sectors, such as the National Oceanic and Atmospheric Association and the Environmental Protection Agency, collect data on various water sources. Yet, the lack of communication among different sectors creates fragmentation of watershed data. As a result, watershed data is widespread, difficult to locate, and sometimes wholly inaccessible. Such fragmentation significantly limits policymakers’ ability to make informed decisions to improve water quality. Neither would consumers be able to tell when their water is unsafe.

One solution is to create open data hubs that centralize accessible and interpretable data, which would require both governmental and nongovernmental efforts. As such, the creation of open watersheds manifests in interesting intersections of community empowerment, resident engagement, and watershed management. In a recent panel discussion titled “Open watersheds: Innovations in Community Water Data,” four panelists involved in open watersheds in the Midwest discussed the benefits, challenges, and opportunities in open-source environmental monitoring.

This panel discussion is part of the monthly Water Data Forum webinar series, co-hosted by the Midwest Big Data Innovation Hub, the Cleveland Water Alliance, and the Water Environment Federation. The participating panelists were Whitnye Long-Jones, founder and executive director of Organic Connects; Mark App, project manager of the Great Lakes Data Watershed; Barb Horn, expert facilitator and steering committee member of the Water Data Collaborative; and Brandon P. Wong, president and co-founder of Hyfi.

Envisioning Open Watersheds

Each panelist had their own vision for open watersheds. Despite coming from different backgrounds, all agreed on the importance of recruiting community effort. Wong spoke from a technological standpoint by relating open-source technologies to open watersheds. He said: “I think there’s a responsibility to see what’s going on underneath the hood.” When it comes to open watersheds, there should be transparency in the process, from data collection from physical devices to data storage. Wong believes that open technologies will allow people to speak openly about what they know about the watershed, knowing how the data is collected and processed.

Long-Jones mentioned creating connections with community members. Since data scientists tend to use jargon and terminologies to describe water data, it is crucial to train community members to make water data more interpretable. Horns reciprocated this point and talked about cultivating relationships between residents and institutions.

Tools for Open Watersheds

Panelists further discussed building connections and relationships when talking about different tools that can benefit the communities. Horn made a crucial point about building healthy relationships with new technologies that facilitate data collection: “Too often technology comes in with its excitement [. . .], but no one has spent that time helping them build the context on how to use it, so it just becomes a strategy that actually has a short-term gain but not long still sustainability even if it could have.”

Horn also explained using data and technology to serve “wholism.” In other words, we should use new technologies to collect data that foster collaboration and innovation. New technologies should not mean to create competitions that only profit a minority of people. “It’s not the community versus the agency or the Agency. It’s not the company industry against the community. It’s like, how can this [new technology] serve wholism? How can this technology serve us coming together in a whol[ly] innovative way?” Horn said.

Regarding the current challenges and barriers, App discussed how the lack of consistent standards in water data collection creates difficulty in data integration. He suggested creating new visions around watershed data. In those visions, data collection would not merely be the responsibility of isolated entities but would be up to the whole community. Skillful community members such as retired NASA engineers, motivated high school students, and computer professionals in pattern recognition can all contribute to monitoring water quality. He believes that those new visions will be the driving force to create open standards in open watersheds.

Open Watersheds and Beyond

The panelists also discussed the benefits of open watersheds beyond open-source data collection and environmental monitoring. Long-Jones emphasized that the community efforts in open watersheds can greatly benefit areas experiencing disinvestment due to historical redlining. “Now you’re seeing some of that even still continuing when we’re talking about cities [that] are experiencing dirty, unclear drinking water,” she said. Many residents in those communities struggle to meet their basic needs, and their survival priorities come before monitoring the contaminants coming out of their faucets.

In this regard, Long-Jones encourages us to envision communities beyond geographic boundaries and be open-minded and humble when engaging with community members bearing diverse backgrounds. Only by truly listening to each other and understanding where each of us comes from can we realize that open watersheds and improving water quality require everyone’s involvement.

Get involved

You can get more involved with open watersheds by participating in the Cleveland Water Alliance’s Smart Citizen Scientist Initiative, a movement that encourages youth, elder, and underrepresented citizen scientists to collect open-source data on Lake Erie with simple technologies. You can also join upcoming Water Data Forum sessions.

Contact the Midwest Big Data Innovation Hub if you’re aware of other people or projects we should profile here, or to participate in any of our community-led Priority Areas, which include Water Quality. The MBDH has a variety of ways to get involved with our community and activities.

The Midwest Big Data Innovation Hub is an NSF-funded partnership of the University of Illinois at Urbana-Champaign, Indiana University, Iowa State University, the University of Michigan, the University of Minnesota, and the University of North Dakota, and is focused on developing collaborations in the 12-state Midwest region. Learn more about the national NSF Big Data Hubs community.