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Profile: Crystal Lu

Nitrogen reduction in the Upper Mississippi River Basin

By Katie Naum

As extreme climate events become more frequent, some of their impact is visible—like the derecho that tore through Iowa in August 2020, leaving a wake of destruction in its path. Other impacts—including nutrient pollution in water systems—are less understood. In what ways will climate change affect the world around us? How can we use data science to better understand and adapt to the impact of climate extremes? 

Chaoqun (Crystal) Lu portrait
Chaoqun (Crystal) Lu

Chaoqun (Crystal) Lu is a quantitative ecosystem ecologist and assistant professor at Iowa State University, and a collaborator of the Midwest Big Data Innovation Hub. Her work focuses on water quality modeling, including the impact of extreme climate events and human activities on nutrient pollution. Her recent NSF CAREER award is titled “Understanding the dynamics and predictability of land-to-aquatic nitrogen loading under climate extremes by combining deep learning with process-based modeling”. The project will bridge the gaps between science and practice, sharing the most current knowledge of Earth system modeling to the public and making the complex concept of watershed management more concrete for the next generation of scientists, land managers, policy makers, and voters.

I spoke with Lu recently via Zoom to learn more about her work with water quality data. The following conversation has been edited and condensed for clarity.

Why is it important to study water quality here and now?

In the United States, nearly 60% of coastal rivers and bays have been degraded by nutrient pollution. Here in the Midwest, people have invested a lot of money and effort over the years to reduce nitrogen pollution. At the same time, climate-driven variations may far outweigh the effects of these nitrogen reduction practices. Increasing summer humidity, more frequent heavy rainfalls, and extreme floods have become a new normal in the central United States over the past few decades. There are a lot of unknowns about how extreme climate events have affected nitrogen leaching from soil and nitrogen loading through tiles, streams and rivers. Lots of data exist, though! 

Policymakers need science-based management suggestions. As a researcher, I would like to benchmark my model with long-term measurements of water quality, and scale up from site-specific measurements to a broader region such as the Upper Mississippi River Basin. If we can figure out how to reduce nitrogen pollution here in the Midwest, the solution we come up with will be very likely to be effective elsewhere. 

Can you tell readers more about the focus of your work, including your recent NSF CAREER award? (Congrats!)

I’m engaged in water quality modeling projects—studying, for example, the impact of nitrogen reduction practices on water quality. Our research team uses mathematical models to represent the physical processes involved in connected systems—the flow of water, the amount of nutrients used by plants or lost to runoff. We also quantify how climate change, land uses, and human management practices could affect nitrogen loading, and assess the effectiveness of nitrogen reduction practices in cleaning water.

The focus of this CAREER award is on how extreme climate events may affect nitrogen loading. My team wants to see how sensitive nitrogen leaching and loading are to events like these, which are increasing in the Midwest. We’re integrating machine learning approaches with a traditional process-based hydroecological model, using a large volume of water quality monitoring data that drains from various sized watersheds in the upper Mississippi–Ohio river basin. I want the key processes represented by traditional process-based models to be kept for water quality prediction, and at the same time improve the models’ outputs with “big data” and machine learning. Our integrated model uses data on water quality, weather, land cover, and human management practices, to better understand whether and where there are nitrogen pollution hotspots in the region. 

What are some of the challenges in working with water data? What are the insights you hope to gain from your research?

One important challenge is just the enormous amount of variation in the data. If you look at a time series for hydrological flow, you see huge variation in the relationship between flow and nitrogen concentration. The challenge we have is to quantify how varied and why. Why do some small watersheds have larger variations than others? Why are some regions more sensitive to climate than others? Is this pattern we’re seeing caused by a specific event, or the legacy of many such events over time? We want to get the whole picture on nitrogen dynamics, from vegetation to soil to water to rivers, from small to large watersheds, at daily time steps, using modeling to recreate such processes.

In our work under this award, we’re planning to include more small watersheds and high frequency data sets. I’m looking forward to new insights from such data analysis. There is so much data over the past few decades to work with, and the technology of water quality monitoring has really improved.

How does deep learning contribute to watershed management?

Deep learning has been transformative for hydrological science and earth system science, yet few studies have used it to digest the big data of water quality monitoring. Meanwhile, high-frequency water quality monitoring data are increasingly available, especially in smaller watersheds and at shorter time scales. This brings new opportunities to test the relationship between flow and nitrogen concentration in response to climate extreme events. All of this motivates me.

Do you consider yourself a data scientist as well as an ecologist? 

I consider myself an ecosystem ecologist, with data science skills. The question I want to find answers to are mostly ecological questions. Sustainability science, biogeochemical cycles, climate variability, natural and human drivers—these are all ecology questions. I say this even though I received training in ecosystem modeling and geospatial analysis for many years—but I consider these tools, the same way I consider machine learning a tool. I always keep my eyes open for tools that can help answer the ecological questions I care about. I tell my students this too: even if their degree or job title says ‘ecosystem modeler,’ I always hope they will step back and see the big picture.

How might interested stakeholders learn more or get involved?

We’ll be developing a project webpage where we will release research findings, future publications, and other relevant materials. Our results will be presented and disseminated to interested stakeholders through our collaborating institutions—not only to academic investigators, but also to the general public, because they are the people who actually make decisions on managing the land and improving the environment. 

This is a very multidisciplinary project, and others may have different ways of thinking about and analyzing the problem that we haven’t considered. We would love to hear from other researchers interested in analyzing the problem from another angle. We are also working actively to seek collaborators and more grants to leverage this project, putting available data sources online to allow easy access.

What do you love most about your research?

Being a modeler is a very precious role. Through multi-scale modeling, we try to connect a lot of different people—field scientists, computational experts, engineers, economists, stakeholders, and policy makers—who can work together to understand and build a more sustainable world for us to live in. This provides a lot of opportunity to collaborate with people in different fields. As a quantitative ecosystem ecologist and ecosystem modeler, I can serve as a bridge between field scientists, extrapolating their findings, and decision makers, who want to see and understand ecological outcomes. The work is really useful and applicable in real life. I enjoy the endless possibilities and the feeling that my research is useful and applicable for our world.


Katie Naum writes on science & technology, climate change, and culture. Follow her @naumstrosity and read more at katienaum.com.


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

Midwest water researchers explore COVID-19 in wastewater

This story is part of a series on coronavirus research in the Midwest region

Researchers in the Midwest are looking in a surprising place for clues about the COVID-19 pandemic: wastewater.

Because so many people who are infected with COVID-19 are asymptomatic, scientists are interested in measuring the prevalence of the SARS-CoV-2 coronavirus in wastewater as a way to understand the population-level spread of the virus in communities. In-person testing can be problematic for a variety of reasons, so researchers are interested in alternatives.

Minnesota Public Radio interviewed one research group that is exploring new ways to explore coronavirus spread without directly testing people. “We’ve decided that one of the easiest ways to do that would be to noninvasively kind of scan the population for the presence of the virus,” University of Minnesota professor Glenn Simmons Jr. said. “And one easy way of doing that would be to look at the wastewater.”

Simmons, along with his collaborator Richard Melvin at UMN Duluth, are testing samples collected from wastewater treatment facilities for the presence of genetic material from the SARS-CoV-2 virus. Other researchers in the Midwest are working on similar sample collection, data analysis, and developing new tools and resources.

One resource under development is a publicly accessible, web-based Wastewater Pathogen Tracking Dashboard (WPTD). Dr. Rachel Spurbeck, research scientist at the non-profit Battelle Memorial Institute in Columbus Ohio, leads the creation of this project.

“The WPTD program is tracking SARS-CoV-2 and other viral pathogens found in the wastewater of four different locations in Toledo, Ohio over time and comparing the sequencing results to the public health and demographic data for these sites”, Spurbeck said. “This comparison will be used to generate risk models for COVID-19 spread in the community as well as other viruses present. We will also be identifying mutations in SARS-CoV-2 which will not only tell us that the virus is in the communities being studied, but also if there are any differences in the virus that could enable identification of how the virus is affecting the population and where the virus came from geographically.”

The data collected will be entered into the Wastewater Pathogen Tracking Dashboard for use by local public health officials to aid in identifying where contact tracing will be most useful. The project is funded by the National Science Foundation (NSF).

Since March 2020, the NSF has made hundreds of new awards focused on COVID-19 research to help address the pandemic. The NSF and the four regional Big Data Innovation Hubs collaborated on the creation of the COVID Information Commons resource to bring together information on these projects. Researchers can use the site to help find tools and resources, and to develop collaborations with other researchers.

Other wastewater tracking projects in the Midwest include two led by Kyle Bibby, Associate Professor of Engineering at Notre Dame university in Indiana. Bibby is leading an effort to develop methods to monitor for the presence of SARS-CoV-2 in wastewater and to connect these measurements to epidemiology models. Bibby also leads a project to create a national Research Coordination Network (RCN) focused on wastewater surveillance, in collaboration with partners from Howard University, Stanford University, Arizona State University, and the Water Research Foundation.

At the national level, the U.S. Centers for Disease Control and Prevention (CDC) has announced the development of a National Wastewater Surveillance System (NWSS) that collects data from local, state, tribal, and territorial health departments to supplement the efforts above.

Get involved

Contact the Midwest Big Data Innovation Hub if you’re aware of other projects we should include here, or to participate in any of our community-led Priority Areas.

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

Introducing the COVID Information Commons

The Midwest Big Data Innovation Hub collaborated with the other three regional Big Data Innovation Hubs and the National Science Foundation (NSF) to launch the COVID Information Commons (CIC).

Funded by NSF COVID Rapid Response Research Award #2028999, the CIC is an open website to facilitate knowledge sharing and collaboration across various coronavirus research efforts, especially focusing on NSF-funded COVID Rapid Response Research (RAPID) projects.

The CIC serves as a resource for researchers, students, and decision-makers from academia, government, not-for-profits, and industry to identify collaboration opportunities and accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic.

WATCH: The recording of our launch and demo webinar is available at covidinfocommons.net as well as on YouTube.

LEARN MORESlides from the webinar are available at covidinfocommons.net, below the July 15 launch + demo video. While you’re there, you can explore the live site!

JOIN THE COMMUNITY: The CIC Slack community is a space for discussion and collaboration among PIs and other stakeholders engaged in COVID research.

We will be announcing further CIC events to showcase lightning talks from 40+ PI volunteers over the next few months. If you are interested in hearing more and did not opt-in at registration for future email updates, you may sign up here.

If you have any questions, please email us at info@covidinfocommons.net

Midwest Big Data Innovation Hub announces leadership changes

As its second year of new funding begins, there is new leadership at the Midwest Big Data Hub (MBDH), with a swap in principal investigators and the appointment of a new executive director. Catherine Blake, a co-principal investigator (PI) on the project, has moved into the PI role, while William (Bill) Gropp transitions to co-PI duties. Long-time Hub staff member John MacMullen was named executive director in January.

Catherine Blake

Blake is an associate professor in the School of Information Sciences (iSchool) at the University of Illinois at Urbana-Champaign, with an affiliate appointment in the Department of Computer Science. At the iSchool, she serves as associate director of the Center for Informatics Research in Science and Scholarship (CIRSS) and director of the graduate programs in information management and bioinformatics. Gropp is director and chief scientist of the National Center for Supercomputing Applications (NCSA) and the Thomas M. Siebel Chair in the Department of Computer Science at Illinois. Prior to joining the MBDH, MacMullen was a faculty member in the iSchool.

“I’m excited and honored to step into the role of principal investigator for the Midwest Big Data Hub,” said Blake. “The community developed during the first phase has made the MBDH well positioned to leverage the rapidly growing data and information collections and technologies in Phase 2 that focus on opportunities, interests, and resources that are unique to the Midwest.”

The MBDH, co-led by the NCSA and the iSchool, serves a twelve-state region that encompasses Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin. It is part of the National Science Foundation’s regional Big Data Innovation Hub (BD Hubs) program that comprises offices in the Midwest, West, South, and the Northeast. Initially funded in 2015, the second phase started in summer 2019 and will run until 2023. The goal of the MBDH awards, which will total over $4 million for both phases, is to catalyze data science efforts around important priority areas in the Midwest.

“This month we’re starting our second year of the new phase of the Hub with the launch of our Community Development and Engagement funding program,” said MacMullen. “We look forward to continuing to develop a vibrant and diverse data science community in the Midwest that includes the range of academic institutions in the region, and grows participation from nonprofits, government agencies, and industry partners.”

Priority areas for MBDH currently include advanced materials and manufacturing; water quality; big data in health; digital agriculture; and smart, connected, and resilient communities. In addition, MBDH leads cross-cutting initiatives to broaden the participation in data science education, develop cyberinfrastructure for research data management, and address cybersecurity issues around big data. MBDH engages with the BD Hubs Data Sharing and Cyberinfrastructure Working Group, the Open Storage Network, and other initiatives that foster access to research data under FAIR (findable, accessible, interoperable, reusable) principles. By leading initiatives in data science education and workforce development, the MBDH aims to increase data science capacity within the region, such as by growing a network of predominantly undergraduate institutions and minority-serving institutions.

“The MBDH is building on the momentum of its first phase by growing the stakeholder community in the Midwest,” said Gropp, who began as PI of the Hub in 2017. “At the same time, we’re actively participating in the evolution of the national data science ecosystem. I look forward to continuing to develop long-term sustainability for the Hub’s activities through strategic projects such as the COVID Information Commons collaboration between the Hubs and NSF, launching in July 2020.”

Follow MBDH on Twitter: @MWBigDataHub

The Midwest Big Data Innovation Hub was initially funded under NSF award #1550320. The current Phase 2 award is #1916613.

Midwest Big Data Hub successfully transitions to second phase with new NSF award

The National Science Foundation (NSF) this month announced the second phase of funding for the regional Big Data Innovation Hub (BD Hubs) program. Under the planned four year, $4 million award, the Midwest Big Data Hub will continue to be led from the National Center for Supercomputing Applications (NCSA) at the University of Illinois, Urbana-Champaign. The Hub’s priority focus areas will be co-led by five partner institutions in the region: Indiana University, Iowa State University, the University of Michigan, the University of Minnesota – Twin Cities, and the University of North Dakota.

First funded in 2015, the four regional BD Hubs were designed by NSF to follow U.S. Census Regions, with offices in the Midwest (led by Illinois), West (UC Berkeley), South (Georgia Tech and UNC Chapel Hill) and the Northeast (Columbia University). The Midwest Hub serves a 12-state region that encompasses Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, North Dakota, Ohio, South Dakota, and Wisconsin.

“Developing innovative, effective solutions to grand challenges requires linking scientists and engineers with local communities,” said Jim Kurose, Assistant Director for Computer and Information Science and Engineering at the National Science Foundation, which funded these awards. “The Big Data Hubs provide the glue to achieve those links, bringing together teams of data science researchers with cities, municipalities and anchor institutions.”

“The Midwest Big Data Hub has built a strong network of partners and a diverse community of stakeholders in the region,” said Bill Gropp, Principal Investigator for the award. “The Hub is well positioned to continue its record of fostering innovative partnerships and providing valued services to our stakeholders in its next phase. Our partner institutions are leaders in the region, and each brings unique strengths to the priority areas they lead.”

The Midwest Hub’s priority areas currently include:

  • Advanced Materials and Manufacturing – Led by the University of Illinois, this area focuses on next-generation materials research in a manufacturing context, and complements the 2016 NSF Big Data Spoke awards on integrative materials design (iMaD) to Northwestern University, the University of Chicago, the University of Illinois, University of Wisconsin – Madison, and the University of Michigan, as well as leveraging existing partnerships with the Materials Data Facility, the nanoMFG node at UIUC, and the Center for Hierarchical Materials Design (CHiMaD) at Northwestern University, all supported by NSF.
  • Water Quality – Led by a new Phase 2 partner, the University of Minnesota – Twin Cities, this area complements the existing water cyberinfrastructure focus of the MBDH through the NSF Big Data Spoke awards made in 2018 to Iowa State University, the University of Illinois, and the University of Iowa.
  • Big Data in Health – The University of Michigan will continue to lead this area, with contributions from Indiana University, building on prior work in Phase 1 as well as the Spoke awards for the Advanced Computational Neuroscience Network (ACNN).
  • Digital Agriculture – Iowa State University will lead this area, with continuing contributions from the University of North Dakota, the University of Nebraska, the University of Illinois, and other partners, including from the 2016 Spoke award for Unmanned Aircraft Systems, Plant Sciences and Education (UASPSE), to continue to build a vibrant stakeholder community engaged with transdisciplinary issues around data for agriculture, food production and plant and animal science.
  • Smart, Connected, and Resilient Communities – Led by Indiana University with contributions from Iowa State University, the University of Michigan, and the University of Illinois, this area continues to build a network and connect resources at the intersection between research and data-driven community decision-making.  

“By catalyzing partnerships that integrate academic researchers into the fabric of communities across the U.S., we can accelerate and deepen the impact of basic research on a range of societal issues, from water management to efficient transportation systems,” said Beth Plale, one of the National Science Foundation program directors managing the Big Data Hubs awards.

The Midwest Hub also leads cross-cutting initiatives for broadening participation in data science education, cyberinfrastructure for research data management, and cybersecurity issues around big data. MBDH participates in the BD Hubs Data Sharing and Cyberinfrastructure Working Group, the Open Storage Network, and other initiatives that foster access to research data under FAIR (findable, accessible, interoperable, reuseable) principles. By leading initiatives in data science education and workforce development, the MBDH aims to increase data science capacity within the region, in part through a growing network of Predominantly Undergraduate Institutions and Minority Serving Institutions.

The Midwest Big Data Hub was initially funded under NSF award # 1550320. The phase 2 award is # 1916613.

Explore the Hub at http://MidwestBigDataHub.org

Learn more about the BD Hubs ecosystem at http://BigDataHubs.org

The MBDH project office is housed at the National Center for Supercomputing Applications (NCSA), which provides computing, data, networking, and visualization resources and expertise that help scientists and engineers across the country better understand and improve our world. NCSA is an interdisciplinary hub and is engaged in research and education collaborations with colleagues and students across the campus of the University of Illinois at Urbana-Champaign.

For interview requests, general questions, copyright permission and B-roll inquiries contact: publicaffairs@ncsa.illinois.edu.

National Science Foundation (NSF) media contact: media@nsf.gov

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Midwest Big Data Hub co-leads local events for 4th Annual Global Women in Data Science Conference

The Midwest Big Data Hub co-led local participation in the 4th annual Global Women in Data Science (WiDS) Conference, with sponsorship from the National Center for Supercomputing Applications (NCSA) and the University of Illinois. The event was free and open to all. The WiDS Conference, hosted on March 4th at 150 locations around the world, seeks to unite and connect women working in data science fields.

“We were very excited to co-sponsor this with NCSA, and support this inaugural Illinois event for Stanford’s Global Women in Data Science Day,” said Melissa Cragin, Executive Director of the Midwest Big Data Hub. “Partnering with others on events such as the Illinois WiDS allows us to best use our human resources and experts network to broaden participation in data science and Big Data research and education. I was honored to participate and have the opportunity to moderate such a terrific panel of accomplished leaders, who shared their perspectives on data science, data-enabled research, and opportunities for women in this space.”

panel discussion
Faculty panel moderated by MBDH Executive Director Melissa Cragin

The WiDS local events, hosted this year at NCSA, featured a variety of speakers from diverse backgrounds presenting sessions on opportunities for women in data science, technical vision talks, and the variety of data science and technology careers available in the Midwest.

“I always enjoy telling my story about how I got started working big data research,” said Ruby Mendenhall, Illinois Professor of Sociology and African-American Studies and NCSA faculty affiliate. “My story also demonstrates the importance of doing outreach to groups that are not traditionally represented in data science such as African American Studies.”

As part of her 2017-2018 NCSA Faculty Fellowship, Mendenhall and NCSA research programmer Kiel Gilleade completed a pilot study called the Chicago Stress Study that examines how the exposure to nearby gun crimes impacted African American mothers living in Englewood, Chicago. Mendenhall and Gilleade developed a mobile health study which used wearable biosensors to document 12 women’s lived experiences for one month last fall. As part of their research, Mendenhall, Gilleade, and their team were able to create an exhibit based on the study data they collected in order to bring the unheard, day-to-day stories of these mothers to life.

panel discussion
Panel discussion moderated by iSchool Professor Catherine Blake

Professor Donna Cox, Director of NCSA’s Advanced Visualization Lab, was a panelist at this year’s local conference, and praised the insights of the other speakers while emphasizing the importance of the larger WiDS conference. “It was valuable to hear other panelists,” said Cox. “The future of Women in Data Science should include raising awareness about important issues emerging in data science, especially socially-relevant issues. We need more women actively involved in the ethics of data science.”

Alice Delage, Associate Project Manager for NCSA and Program Coordinator for the MBDH, said, “Hosting WiDS Urbana-Champaign at Illinois was an opportunity to highlight the campus expertise around data science led by women.” Delage, who co-chairs the local Women@NCSA group, said, “Data science and technologies are increasingly impacting our lives and society, and it is imperative that women and minorities be part of these transformations. We wanted to showcase the groundbreaking work being done in that area by Illinois female data scientists and to inspire more women and underrepresented communities to engage in the field.”

There are also opportunities to expand the event next year by better incorporating student work in the program, Delage said, or running a datathon, for example. Some of this year’s participants have already volunteered to help with next year’s event.

A full list of this year’s speakers at the WiDS Conference at NCSA is here. For more information about the global WiDS conference and ways to get involved, please visit https://www.widsconference.org.

The MBDH is one of four regional Big Data Innovation Hubs with support from the National Science Foundation (award # 1550320), and works to build capacity and skills in the use of data science methods and resources in the 12-state U.S. Midwest Census region. Learn more about the Hub at https://midwestbigdatahub.org.

Thanks to NCSA Public Affairs for contributing to an earlier draft of this post.

BD Hubs profiled in SIGNAL magazine

The NSF-funded Big Data Innovation Hubs were highlighted in a recent article in SIGNAL magazine, a publication of the AFCEA (Armed Forces Communications and Electronics Association). The Executive Directors of the Midwest and Northeast Big Data Hubs, Melissa Cragin and René Baston, were quoted extensively from interviews that covered the wide-ranging communities and activities of the Hubs. Here is an excerpt from the article:

“[W]hile we’re called the Big Data Innovation Hubs, we’re very focused on building capacity in data science, building expertise, access to data-related services and networks related to all things data science,” said Cragin.

That means making available “to all kinds of communities” access to data-related skills, services, tools and opportunities, Cragin states. By developing public/private partnerships and working with groups to leverage these resources, the hubs can help coordinate solutions to “shared grand challenges,” she notes. The hub also is endeavouring to extend data science research and education to predominantly undergraduate institutions—including minority-serving institutions—to help add data skills for the developing workforce, she states.

The regional aspect allows each hub to identify priority areas or “spokes” that they are pursuing. For the Midwest, issues relating to water quality; digital agriculture and unmanned aerial systems; and food, energy and water, among others, play a major role.

Read the full article here.

Guest post – Diverse programs from ISU address sustainable cities challenges

By Iowa State University’s Sustainable Cities team

Researchers with the Sustainable Cities team at Iowa State University recognize the difficulty that public officials face in transforming vast amounts of climate and energy research into contextualized public policy. In attempting to address this critical issue, the team’s mission goes beyond the creation of new climate analysis tools to also investigate new methods for integrating communities into the discourse of data creation and energy conservation. To accomplish this agenda, our team engages in various research avenues that range from the creation of new spatial-data tools to enabling community youth activism. Here are just a few highlights of the team’s most recent achievements:

Sustainable Cities’ team leader Ulrike Passe, associate professor of architecture, presented our hybrid physics data modeling framework at the National Science Foundation-sponsored Research Coordination Networking (RCN) workshop held at Carnegie Mellon University on May 17, 2018. The presentation, which capstones one of the major branches of the Sustainable Cities initiatives, demonstrated the integration of our recently developed thermo-physical data simulator with our research into human energy-use behavior to demonstrate how a more holistic neighborhood energy model could be constructed. This same model was presented by graduate research assistant Himanshu Sharma at the fifth High Performance Building’s Conference on July 9, 2018, at Purdue University.

image from Krejci et al. (2016)

The Community Growers Program, a public-engagement initiative started back in March of 2017, has become another core pillar of the Sustainable Cities group research. Spanning a course of eight weeks, researchers worked with 22 leadership-minded youth in the Baker Chapter of the Boys and Girls Club at Hiatt Middle School in Des Moines, Iowa, to create a community garden based on a methodology of spatial, socio-technical storytelling. Through this process, the youth participants were able to learn more about their community through access to geographic information system (GIS) and spatial mapping tools. Associate English professor Linda Shenk, our community engagement lead, and Mallory Riesberg, a collaborator with the Baker Chapter of the Boys and Girls Club, presented this methodology in a presentation titled, “Fostering the Next Generation of Big Data Scientists and Sustainable City Planners” at The Growing Sustainable Communities Conference in Dubuque, Iowa, on Oct. 4, 2017. Team members Linda Shenk, Passe and Alenka Poplin, assistant professor of community and regional planning, would later be published in the 35th Journal of Interaction Design and Architectures for the inclusion of this work in their entry, titled, Engaging Youth with Pervasive Technologies for Resilient Communities.

Poplin, an established researcher in the field of geo-spatial mapping, also leads a research group that seeks to understand how to better develop feedback loops through innovative user-interfaces. An inquiry into mapping places of emotional power was highlighted in a 2017 paper entry to the second edition of Kartographische Nachrichten on Empirical Cartography Journal, titled, “Mapping Expressed Emotions: Empirical Experiments on Power Places.” More recently, Poplin and her researcher team have begun testing an energy survey game they have developed called E-Footprints. The framework of this game includes the extraction of user-performance data to measure and analyze what learning opportunities may help guide more environmentally efficient decision making. This feedback is then generated back into learning mini-games throughout the game, such that the user gets more “energy savvy” as they play. This project begins field-testing in November 2018.

With a diverse, multifaceted research team of nearly 50 members, the Sustainable Cities group continues to advance the capabilities of communities and cities to think sustainably about a better future.

 

Image reference:

Krejci, C. C., Passe, U., Dorneich, M. C., & Peters, N. (2016), “A Hybrid Simulation Model for Urban Weatherization Programs”, Proceedings of the 2016 Winter Simulation Conference, Arlington, VA, December 11–14. T. M. K. Roeder, P. I. Frazier, R. Szechtman, E. Zhou, T. Huschka, and S. E. Chick, eds. (pdf)

 

Read more about the MBDH’s Smart, Connected, and Resilient Communities initiatives.

Guest post – Data Science Education at Two-Year Colleges

By Matt Fall

Executive Director, Center for Data Science, Lansing Community College

Recently, the American Statistical Association (ASA), with support from the National Science Foundation (NSF), hosted a two-day summit in Washington D.C. to discuss outcomes and curricula for data science programs at two-year colleges. The Two-Year College Data Science Summit (TYCDSS) was intended to help spur the growth of data science programs at these institutions and included representatives from two and four-year institutions, government, and industry.

Sallie Keller (Virginia Tech) plenary talk (photo: Nicholas Horton)

The summit included several plenary talks discussing the role of two-year colleges in addressing the need for data scientists as well as a brief presentation from a graduate of a community college data science program. The majority of the summit, however, was devoted to a series of working sessions where the participants discussed ideal outcomes and competencies for three categories of students:

  • Category 1: students intending to complete an Associate’s degree and begin working
  • Category 2: students intending to earn an Associate’s degree and transfer to a 4-year program
  • Category 3: students seeking a certificate

The working discussions provided an opportunity for the summit participants to discuss what was expected and feasible for a student from each category to complete. The discussions were captured by a designated writing group and there will be a forthcoming write-up summarizing the recommendations of the summit participants with guidelines for two-year college data science programs.

This summit was particularly timely for my colleagues at Lansing Community College (LCC) as we have recently begun development of a data science program. Prior to the summit, participants were provided access to a list of resources that included relevant research, reports from related workshops, and sample syllabi. Of particular interest to us, as we design the layout of our program, were the Park City Math Institute’s Curriculum Guidelines for Undergraduate Programs in Data Science (2016) [PDF], the Oceans of Data Profile of the Data Practitioner (2016), and the Oceans of Data workshop report on Building Global Interest in Data Literacy (2016). The resources provided, candid discussions with other two-year colleges regarding their programs, and the discussions about realistic competency expectations were also of interest and informative to our program design.

The intent of the TYCDSS directly supports the MBDH’s priority area of interest in data science, education and workforce development. Two-year colleges provide higher education accessibility to many students who could not or would not otherwise pursue an advanced degree. An increasing number of these schools are offering certificate and Associate’s degree programs in data science and analytics to support growing workforce demand. Growth in these types of programs should naturally lead to an increase in data competency, enrollment in university programs, and larger hiring pools for data science based careers.

Related information:

Guest post – URSSI: Conceptualizing a US Research Software Sustainability Institute

First URSSI workshop attendees (Credit: Mike Hucka)

Contributed by Daniel S. KatzJeff CarverSandra GesingKarthik RamNic Weber

 

The NSF-funded conceptualization of a US Research Software Sustainability Institute (URSSI) is making the case for and planning a possible institute to improve science and engineering research by supporting the development and sustainability of research software in the US.

Research software is essential to progress in the sciences, engineering, humanities, and all other fields. In many fields, research software is produced within academia, by academics who range in experience and status from students and postdocs to staff members and faculty. Although much research software is developed in academia, important components are also developed in national laboratories and industry. Wherever research software is created and maintained, it can be open source (most likely in academia and national laboratories) or commercial/closed source (most likely in industry, although industry also produces and contributes to open source.)

The open source movement has created a tremendous variety of software, including software used for research and software produced in academia. This plethora of solutions is not easy for researchers to find and use out-of-the-box. Standards and a platform for categorizing software for communities are lacking, which often leads to novel developments rather than reuse of solutions. Three primary classes of concern are pervasive across research software in all research disciplines and have stymied research software from achieving maximum impact:

  • Functioning of the individual and team: issues such as training and education, ensuring appropriate credit for software development, enabling publication pathways for research software including novel methods beyond “classical” academic publications, fostering satisfactory and rewarding career paths for people who develop and maintain software, increasing the participation of underrepresented groups in software engineering, and creating and sustaining pipelines of diverse developers.
  • Functioning of the research software: supporting sustainability of the software; growing community, evolving governance, and developing relationships between organizations, both academic and industrial; fostering both testing and reproducibility, supporting new models and developments (for example, agile web frameworks, software as a service), and supporting contributions of transient contributors (for example, students).
  • Functioning of the research field itself: growing communities around research software and disparate user requirements, avoiding siloed developments, cataloging extant and necessary software, disseminating new developments, and training researchers in the usage of software.

The goal of this conceptualization project is to create a roadmap for a URSSI to minimize or at least decrease these types of concerns. To do this, the two aims of the URSSI conceptualization are to:

  1. Bring the research software community together to determine how to address the issues about which we have already learned. In some cases, there are already subcommunities working together on a specific problem, including those that we are part of, but those subcommunities might not be working with the larger community. This leads to a risk of developing solutions that solve one issue but don’t reduce (or might even deepen) other concerns.
  2. Identify additional issues URSSI should address, identify communities for whom these issues are relevant, determine how we should address the issues in coordination with the communities, and determine how to prioritize all the issues in URSSI.

We are not working in a vacuum, but with other like-minded projects. In addition to Better Scientific Software (BSSw) and activities around research facilitators (ACI-REF) in the US, there are two ongoing institutes in science gateways (SGCI) and molecular sciences (MolSSI); a recently completed conceptualization in high energy physics (S2I2-HEP); two other conceptualization projects now underway in geospatial software and fluid dynamics; and a large number of software development and maintenance projects. In the UK, the Software Sustainability Institute (SSI), which has been in operation since 2010, is an inspiration and a potential model for our work.

Given these existing activities, part of our challenge is to define how we will work with these other groups. For example, we might decide that they perform an activity so well that we should point to it, such as the SSI’s software guides. Or we might decide to either duplicate or enhance an activity they do to expand its impact, such as working with the SGCI to offer incubator services to a wider community than just gateway developers. Or we might decide to collaborate with one or more groups, such as on policy campaigns aimed at providing better career paths for research software developers in universities.

We have held one workshop and are planning three more, in addition to a community survey we plan to have out soon, and a set of ethnographic studies of specific projects. We are communicating through our website, a series of newsletters, and a community discussion site.

URSSI welcomes members of the research software community to join us, both to help us determine how to proceed and to directly contribute. Please sign up for the URSSI mailing listcontribute to our discussions, and potentially publish a guest blog post on the URSSI blog on a topic around software sustainability.

Welcome to the new MBDH Community Blog

Greetings!

Today we are launching a new MBDH Community Blog, which is intended to extend information sharing around events and projects, as well as expand our channels for Community conversation.

We plan to run 1-2 posts per month, and we are now seeking submissions from the MBDH Community – including the Spokes and our other collaborative projects – that describe your contributions and developments in the broader data ecosystem. Of interest are short reports and highlights from data-related meetings, events, or project outcomes, inclusive of the role and impact of the MBDH for these efforts.

We welcome contributions from the Social Sciences and Humanities, including short contributions that address data and algorithmic ethics, or coming changes for work, daily life, and public engagement in U.S data policy.

We encourage submissions from practitioner and NGO perspectives, as well as those from academia, industry, or government. We will provide additional guidelines shortly. If you are interested in submitting a Blog post, please send your contact information and the subject area to: info@midwestbigdatahub.org

Our first guest post is by Daniel Katz, Assistant Director for Scientific Software and Applications at the National Center for Supercomputing Applications (NCSA). Check out his post on the US Research Software Sustainability Institute (URSSI) project.

Finally, I’ll note a couple of activities where we are currently seeking input and engagement:

Add your voice to our Midwest Big Data Hub evaluation

  • To create a robust strategic plan for the Midwest Hub.
  • To plan toward long-term sustainability, especially financial sustainability, for the Midwest Hub.
  • Provide your input here: https://www.surveymonkey.com/r/MBDHSurvey

Participate in our election of five (5) At-large representatives for the MBDH Steering Committee:  https://midwestbigdatahub.org/2018-steering-committee-at-large-nominees/

As always, please contact us with any ideas or questions.
Thank you for your continued support!

All the best,
Melissa Cragin
Executive Director, Midwest Big Data Hub

Midwest Big Data Summer School 2018

Midwest Big Data Summer School reveals how big data can advance research efforts

By Paula Van Brocklin, Office of the Vice President for Research, Iowa State University

Iowa State University logo
The Midwest Big Data Summer School, held May 14-17 at Iowa State University, helped nearly 140 academic and industry researchers, graduate students and post-docs from nine states broaden their understanding of big data and its ability to advance their research interests. Iowa State has organized and hosted the event since 2016.

 
“The summer school seeks to bridge the gap between scientists and engineers using data science technology by introducing them to data science techniques and vocabulary,” said Hridesh Rajan, lead organizer of the Midwest Big Data Summer School and professor of computer science at Iowa State. “The idea is to help these individuals better communicate and leverage their data-science needs.”

The curriculum

The school’s first three days introduced attendees to a range of big data topics, including data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding domain/context.

On the final day, participants selected one of four tracks, which focused on a sub-area of big data analysis. The tracks were:

  • Foundations of Data Science
  • Software Analytics
  • Digital Agriculture
  • Big Data Applications

Several individuals at Iowa State were instrumental in developing and organizing the tracks’ curricula. Click here for a list of those involved.

Speakers

Keynote presenters at this year’s summer school were:

  • Chid Apte, director, Mathematical Sciences and Blockchain Solutions, IBM Research
  • Tom Schenk, chief data officer, City of Chicago
  • Jacek Czerwonka, principal software engineer, Microsoft Research
  • Will Snipes, principal scientist, ABB Research

A complete list of speakers, including their bios, is available here.

Data science evolving quickly

The field of big data, also referred to as data science, is relatively new yet advancing quickly. For this reason, organizers encourage researchers and scientists to learn as much as they can through resources like the Midwest Big Data Summer School.

“Our aim is for early career researchers and professionals – both in academia and industry – to get a taste of what it’s about, what the state of the art is and how they can start thinking about using data science in their own domains,” said Chinmay Hegde, assistant professor of electrical and computer engineering at Iowa State and a co-organizer of the summer school.

Many thanks

Rajan recognizes the summer school would not be possible without the help of many.

“We are especially thankful for the Midwest Big Data Hub, the National Science Foundation, the Office of the Vice President for Research, Iowa State’s College of Liberal Arts and Sciences, and the departments of computer science and statistics for providing both funding and personnel support for this event.”

Next year
Plans are in the works for the 2019 Midwest Big Data Summer School, though no dates have been set. Rajan said more application-specific tracks may be added to next year’s curriculum. Watch the Midwest Big Data Summer School website for more details in the spring of 2019.

——

Reposted from Iowa State University’s Research News blog. View the original post here.

Big Data Hubs partner with NSF and JHU on new nationwide data storage network

The Midwest Big Data Hub and the three other regional Big Data Innovation Hubs are partnering with the National Science Foundation and Johns Hopkins University on development of a new nationwide research data network called the Open Storage Network. Partners include Alex Szalay, lead PI (Johns Hopkins), Ian Foster (University of Chicago), the National Data Service (NDS), and five supercomputing centers within the Big Data Hubs’ regions.

The official NSF press release is available here.

The Johns Hopkins story is here.

A story from NCSA with more details from Melissa Cragin, MBDH Executive Director and award PI, and NDS Executive Director Christine Kirkpatrick is here.

Links to partners:

Innovating in the Big Data Ecosystem: Public-Private Partnerships for a Data-enabled World

Solving complex data challenges require innovative cross-border, multi-sector partnerships

(This article first appeared in the Spring/Summmer 2018 issue of Current magazine, published by MBDH partner Council of the Great Lakes Region. There is a PDF version here. View the full issue here.)

by Melissa Cragin, Ph.D
Executive Director, Midwest Big Data Hub

Complex data challenges facing the Great Lakes region in the era of big data transcend industries, applications, and borders. While data is increasingly borderless, borders and barriers still present substantial problems to industry, academic, and government initiatives that are dependent on data policy and governance processes that structure access and use. These challenges require innovative cross-border, multi-sector partnerships that can leverage the benefits of shared high performance computing resources and cyberinfrastructure services.Read More

MBDH partners on US Ignite Reverse Pitch challenge

part of Hub’s focus on Smart, Connected, and Resilient Communities

US Ignite Hackathon
UIUC collaborators and mentors meet with HackIllinois teams on US Ignite Challenge

The University of Illinois at Urbana-Champaign (UIUC) was awarded a $20,000 grant from US Ignite to host a Smart Gigabit Communities Reverse Pitch Challenge. The MBDH, along with other local partners (see below), contributed towards matching the grant, bringing to $40,000 the total resources available to support the development of smart gigabit applications for the benefit of the local community. Read More

New Report on “Keeping Data Science Broad”

A new report on the “Keeping Data Science Broad: Negotiating the Digital and Data Divide Among Higher Education Institutions” initiative was released by the South Big Data Hub and collaborators, including the Midwest Hub. This initiative brought together the BD Hubs community and other stakeholders to explore pathways for keeping data science education broadly inclusive. Read More

MBDH 2017 All-Hands Meeting Recap

by Keith Hollenkamp

On October 1-2, we hosted the Midwest Big Data Hub All-Hands Meeting at the beautiful Kiewit University in Omaha, Nebraska. Over the course of the two day event, researchers, academics, students, and more, connected over similar interests and attended panels all centered around this year’s theme: Data-Enabled Midwest Resilience.

Melissa Cragin, Executive Director of the MBDH, welcomes attendees to the All-Hands Meeting

Read More

An Introduction to Dr. William Gropp, MBDH PI

Dear MBDH Community,

I wanted to officially introduce myself as the new PI of the Midwest Big Data Hub. In a previous MBDH newsletter, it was announced that I would be taking over the role after the former PI, Dr. Ed Seidel, accepted the job of Vice President for Economic Development and Innovation for the University of Illinois System. It is with great enthusiasm that I join the MBDH community, and I’m eager to contribute to all the ways the Hub is expanding and enhancing the Midwest Big Data ecosystem.

Read More

Machine Learning: Farm-to-Table Workshop

by Keith Hollenkamp –

In April, the MBDH teamed up with the International Food Security at Illinois (IFSI) to host the Machine Learning: Farm-to-Table Workshop. The workshop brought together domain scientists to stimulate new data-driven R+D activity at the intersections of the Agriculture, Bioinformatics, Food-Energy-Water, and Food Security communities.

Read More

A Note From Ed Seidel

Dear Friends and Colleagues of the Midwest Big Data Hub:

I’d like to let you all know that I have recently accepted the position of VP for Economic Development and Innovation for the University of Illinois System, and will no longer be the Director of NCSA. As a result, after consulting with MBDH leadership, NSF, and U of IL officials, we have decided that it is the best interests of the hub that we pass the PI role to Prof. Bill Gropp.

Read More

National Transportation Data Challenge

National Transportation Data Challenge Kicks Off on May 2-3!

The Big Data Regional Innovations Hubs have announced the Transportation Data Challenge, a series of community problem solving-sessions, data faires, hackathons, and demonstrations, held in collaboration with the U.S Department of Transportation, Amazon Web Services, Microsoft, Data Science Inc., and others.

Read More

The Machine Learning: Farm-To-Table Workshop

The Midwest Big Data Hub (MBDH) is partnering with the International Food Security at Illinois (IFSI) group at UIUC to bring together domain scientists from the Agriculture, Bioinformatics, Food-Energy-Water, and Food Security communities, along with computational experts. The objective of this workshop is to stimulate new data-driven R+D activity at the intersections of these communities. The meeting will be structured to enable new cross-community interactions and initiate grant proposals or publications.

Read More

MBDH Spoke Awardee Guides Open Source Computational Research Infrastructure for Science

The newly released open source Computational Research Infrastructure for Science (CRIS) was developed with contributions from a Midwest Big Data Hub (MBDH) Planning Grant, “Cyberinfrastructure to Enhance Data Quality and Support Reproducible Results in Sensors.” CRIS provides an easy to use, scalable, and collaborative scientific data management and workflow cyberinfrastructure.

CRIS was developed at Purdue University under the technical leadership of Peter Baker and the scientific supervision of Professor Elisa Bertino. Dr. Bertino is the PI of the MBDH Planning grant, which contributed by assessing the quality tools and versioning techniques provided by CRIS. Within the grant, the developers are currently working on provenance models and techniques, and provenance interoperability for the CRIS provenance model.

More information can be found here.

Midwest Big Data Hackathon, University of Iowa

October 8–9, 2016
Iowa City, Iowa

The Midwest Big Data Hackathon is a 2-day, non-stop hackathon with 150 participants, and it will be held at University of Iowa—in the heart of downtown Iowa City, USA. The event is open to all university students that have a passion for creating things with technology!

Students will form teams to work on their project (or ‘hack’) up to 4 members. Projects are open format, which means that you can hack on web, mobile, desktop, or hardware applications. Company mentors will be available throughout the event for questions to make sure beginners and experts alike will have the help they need to successfully develop their project. All teams will demo their hacks at the end of the event and winners will be chosen by company mentors.

NSF awards connect Midwest Big Data Hub and scientists to solve regional challenges

Today, the National Science Foundation (NSF) announced $10 million in “Big Data Spokes” awards to initiate research in specific areas identified, supported, and organized by the Big Data Regional Innovation Hubs (BD Hubs). $2.4 million in Big Data Spoke, Early­ Concept Grants for Exploratory Research (EAGER) and planning awards will connect the Midwest Big Data Hub (MBDH) and midwestern data scientists, to support digital agriculture; community-driven and sustainable neuroscience data infrastructure; improved sensor technologies; citizen scientists and real-time air quality monitoring; and new data-to-decision systems in hazards management by partnering data scientists with emergency personnel.

Read More

Data Quality in a Big Data Era

September 28-29, 2016
Cyberinfrastructure Building, Wrubel Lobby, Indiana University
Bloomington, Indiana

What is data quality and what does it mean in the age of big data? Throughout the history of modern scholarship, the exchange of scholarly data was undertaken through personal interactions among scholars or through highly curated data archives, such as ICPSR (Inter-University Consortium for Political and Social Research). In both cases, implicit or explicit provenance mechanisms gave a relatively high degree of insurance of the quality of the data. However, the ubiquity of the web and mobile digital culture has produced disruptive new forms of data such as those based on citizen science, social network transactions, or massively deployed automatic sensors. Integrity and trustworthiness of these data are uncertain due to issues such as sampling characteristics, expertise of the data producers, or quality of the instruments. As these data are shared, fused, homogenized, and mixed, we need to ask ourselves what we know about the data and what we can trust. Failure to answer these questions endangers the integrity of the science produced from these data.

For more information, go to http://d2i.indiana.edu/mbdh.

Registration

There is no cost to attend but space is limited to 50 attendees. Registration will be available from August 5, 2016 until September 19, 2016. Early career scientists and researchers will be selected to predominantly fill available seats.

Travel Support

Travel support—automobile and lodging—for non-IU participants who are working in industry, government, or non-profit sectors is available. Qualified individuals are expected to present their work in a poster session Sept. 28, 2016 to showcase the breadth of developments occurring in Big Data. To be considered, please register by September 9, 2016 and apply for travel support. Application details are available at http://d2i.indiana.edu/mbdh/#scholarships.

Questions about the data quality workshop should be sent to Jill Minor, jsminor@indiana.edu.

Food and Data Workshop: Interoperability through the Food Pipeline

September 12-13, 2016
University of Illinois at Urbana-Champaign

The increasing ability to capture data at the level of individual agricultural fields, individual culinary recipes, and individual food waste digesters is allowing analytics-based optimization within the distinct industries responsible for producing, transporting, trading, storing, processing, packaging, wholesaling, retailing, consuming, and disposing of food. Yet addressing the pressing national/global challenges in food security due to climate change, as well as public health challenges such as obesity and malnutrition, requires optimization across the food pipeline. The Food and Data Workshop: Interoperability through the Food Pipeline, September 12-13 in the CSL Auditorium (B02), is concerned with understanding the relationship between data and food writ large, with a particular focus on questions of interoperable data ontologies, privacy, and analytic insights.

For more information and to register go to https://publish.illinois.edu/food-and-data-workshop/.

Midwest Workshop on Neuroscience Big Data

September 20-21, 2016
Ann Arbor, Michigan

Students, trainees, fellows, junior investigators, and outside researchers in Midwest academic institutions and industry partners are invited to attend and actively participate in the Midwest Workshop on Neuroscience Big Data. Expected workshop outcomes include (1) building an active Midwest Neuroscience Network Community, (2) open-sharing of data-intense challenges, datasets, research projects, expertise, software, services, protocols, resources, learning modules, and (3) productive discussions of joint (multi-institutional) grants, training opportunities, publications, research projects. The workshop success will be measured by assessing the community involvement (early registration, active workshop participation, post-workshop activities and interactions), website analytics (geographic locations of income traffic, counts, frequencies, and intensity of web-site utilization, and evidence of collaborations on development of software tools, services, learning materials, end-to-end pipeline workflows.

Registration is free, but space is limited. Sixty scholarships are being offered to students, post doctoral scholars and early career investigators in form of travel and lodging support to attend the workshop.

Missouri S&T Research and Technology Development Conference

September 12-13, 2016
Havener Center
Rolla, Missouri

Midwest Big Data Hub is hosting an Early Career lightning talk session on the topic of data in a research project setting at the Missouri S&T Research and Technology Development Conference. Travel reimbursement for presenters is available for up to $250/presenter. Pre-tenured faculty, post-docs, graduate students, and undergraduates are encouraged to give a quick 5-minute presentation on any data issue of relevance to a research project in which you participated. Eight to ten lightning talks will be scheduled. Apply today!

Symposium on Frontiers in Big Data

Friday, September 23, 2016 and Saturday, September 24, 2016
University of Illinois at Urbana-Champaign

You are cordially invited to attend the Grainger Foundation-sponsored “Symposium on Frontiers in Big Data” on September 23-24 at the University of Illinois at Urbana-Champaign campus. It is a great opportunity to:

  • Listen to invited talks, interview dialogs, panels, and debates regarding new challenges of Big Data;
  • Explore Big Data Frontiers in Bioinformatics, Agriculture, Systems, Optimization, and Machine Learning, with nationally renowned speakers, including:
    • Michael Franklin (University of Chicago),
    • Al Hero (University of Michigan),
    • Michael Jordan (University of California, Berkeley),
    • James Krogmeier (Purdue University),
    • George Lan (Georgia Institute of Technology),
    • Mihai Pop (University of Maryland),
    • Dana Randall (Georgia institute of Technology),
    • Robert Tempelman (Michigan State University),
    • John Wilkes (Google Inc.);
  • Meet nationally renowned UIUC Big Data researchers and engage in discussions with speakers during the symposium and the reception.

Registration is free but required due to meal planning. Please register by September 8, 2016.

If you have any questions about the Symposium on Frontiers in Big Data, please contact Doris Bonnett (dbonnett@illinois.edu). For more information and the tentative agenda, please visit the Symposium website.

Big Data for Health and Medicine Workshop — August 11, 2016

Join us on August 11, 2016 for a workshop to discuss challenges in using big data for driving health and medicine at the University of Nebraska at Omaha College of Information Science & Technology! Our goal is to encourage discussion on challenges currently facing health-related industries with regards to data collection, gathering, storage, and analysis. We hope to bring together representatives from industry, government, non- profits, and academia to discuss the following current topics of interest for health and medicine:

  • Wearables (FitBit, Jawbone UP, Polar)
  • Quantified Self and IoT
  • Predictive medicine
  • Precision medicine
  • Analytics for health
  • Data collection & storage
  • Data analysis
  • Security concerns
  • Collaboration
  • Smart cities
  • Food for health
  • Reproducibility and robustness
  • Data science
  • …and related topics

In the afternoon we will hold concurrent sessions. The Technical Track will consist of an Introduction to R workshop, designed for participants in industry, government, and non-profit with limited programming background, or with experience in other languages (SAS, SPSS) looking to investigate the open-source R language. This workshop will be free for the first 45 participants. The concurrent Breakout Track will provide opportunities for discussion, collaboration, and sharing their own personal challenges in dealing with data in health-related fields.

Registration is free for the first 45 participants!

Tentative Agenda

9:00A — Welcome and introduction
9:30A — Keynote – Tentative Topic: Big Data Challenges in Health-related Fields
10:30A — Coffee break
10:45A — Keynote – Tentative Topic: Team Science Approaches to Collaboration in Big Data
11:45A — Panel and lunch (*lunch is included with registration)
1:00P

Technical Track
Workshop: Intro to Data Analysis with R*
Audience: Beginner/Intermediate
*Limited to first 30 participants to sign up.

Breakout Track
A number of speakers will be joining us for discussions on high performance computing, green computing, analytics needs, and related topics.

4:00P-5:00P — Reception and Poster Session

Big Data for Health and Medicine Workshop

Thursday, August 11, 2016
9:00am-5:00pm
Peter Kiewit Institute — Omaha, NE

Midwest Big Data Summer School, June 20-24, 2016, Ames, IA

The Midwest Big Data Summer School for Early Career Researchers will be held from June 20-24, 2016 in Ames, Iowa. This summer school is designed as a one week, intensive curriculum aimed at early career researchers to get them started in data-driven research. The school will include full day lectures on topics ranging from: data acquisition, data preprocessing, exploratory data analysis, descriptive data analysis, data analysis tools and techniques, visualization and communication, ethical issues in data science, reproducibility and repeatability, and understanding of domain/context. The summer school is partially supported by the Midwest Big Data Hub, by the ISU College of Liberal Arts and Sciences, by the ISU Office of the Vice President of Research, and by the ISU Department of Computer Science.

Midwest Big Data Summer School
June 20-24, 2016
Morrill Hall, Iowa State University
Ames, IA
http://mbds.cs.iastate.edu/

Registration

There is no cost to attend but you must register by Wednesday, June 1 at 5:00pm to reserve your space. There is limited space so send your registration soon.

Travel Support

We have limited amount of travel support available for non-ISU participants. To be considered for travel support, please register by May 24 at 5:00pm and apply for travel support. Application details are available at http://mbds.cs.iastate.edu/.

We look forward to welcoming you in Ames, Iowa this June 2016. Any questions about the summer school should be sent to Hridesh Rajan, hridesh@iastate.edu. Please do feel free to circulate this to your colleagues as you see fit.

Digital Agriculture Spoke All-Hands Meeting – May 16-17, 2016

Videos of the presentations are now available!

The 2016 Digital Agriculture Spoke All-Hands Meeting to be held on May 16-17 at the Scheman Building, Iowa State Center, Ames, Iowa. The Digital Agriculture Spoke of the Midwest Big Data Hub is devoted to building partnerships and resources that will address emerging Big Data issues in the agricultural ecosystem.

Stakeholders from academia, industry, government, and other organizations will engage in interactive discussions about the partnerships and resources that will be needed to address the challenges in collecting, managing, serving, mining, and analyzing rapidly growing and increasingly complex data and information collections to create actionable knowledge and guide decision-making in agriculture.

Events will include presentations by Midwest Big Data Hub and national leadership; industry panel presentations and Q&A; participant lightning talks; and breakout sessions to discuss existing projects and to develop ideas and partnerships for new projects; and a poster session and reception.

Early career researchers, post-docs, graduate students, and undergraduate students are encouraged to attend. There is no registration fee for this meeting.

UND Early Career Big Data Summit – April 6-8

The University of North Dakota (UND) will host an Early Career Big Data Summit (ECBDS) April 6-8, 2016. This Big Data event seeks to provide a venue for early career Big Data researchers (graduate students, post docs, and pre-tenure faculty) to connect with Industry, third-sector volunteer groups, and established researchers. Events will include multiple industry panel discussions, researcher lightning talks, and a hands-on application hack-a-thon. The Summit is expected to have representation from the Digital/Precision Agriculture, Transportation, Social Media, and Unmanned Aircraft Systems industries.

The summit will be co-located with the 47th Annual UND Writers Conference, whose theme this year is “The Art of Science” (AoS). In addition to Summit events, all attendees will be allowed to attend all AoS events—including Keynote presentations by Brian Greene (string theorist, author of The Elegant Universe, and entertaining communicator of cutting-edge scientific concepts) and award winning science fiction writer Kim Stanley Robinson. While the entire AoS schedule is available on the UND Writers Conference website, additional AoS events include: 1) the Greene post-keynote social event at the North Dakota Museum of Art, and 2) the Thursday afternoon Prairie Public Radio interview and audience question/answer session with Brian Greene on the topic of “How to communicate science to a popular audience.”

The ECBDS has no registration fees, but registration is required for those seeking participant support and/or wishing to participate in hosted panels, lightning talks, or the hack-a-thon. Attendees will be responsible for their own meals, lodging, and travel. A limited amount of participant support is available to registered summit attendees only—preference is given to Big Data Summit presenters. More registration information is available through the ECBDS website.