Category: blog

By Francie Fink

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.

Finding help for health and social services shouldn’t be as difficult as the challenges people already face. Yet, often these services are buried in dead-end mazes of incomplete or outdated information.  Imagine finding help for housing or healthcare as easily as Googling directions to a coffee shop. That’s the vision behind Open Referral’s latest project: a participatory tool kit for building community-resource directories that work—and that truly serve the public good.

The Open Referral Initiative has a clear-but-effective goal: transform access to health, human, and social services by developing data-sharing standards to make community resources a public good. If we think back to Econ 101, resource information as a public good means it’s accessible to everyone, and one person or organization’s use of it doesn’t reduce its usefulness for others; however, nobody is inclined to pay for it. This presents dilemmas. So, although there are many tactical questions pertaining to the technical details of any given resource directory, Open Referral is focusing on strategic questions of institutional design: ways in which communities can agree on a shared approach to supplying resource-directory data as an open, infrastructural resource that is accessible by all.

Greg Bloom is a visiting scholar with the Ostrom Workshop at Indiana University, and also leads the Open Referral Initiative. Bloom’s inspiration for Open Referral actually stems from firsthand experience with maintaining resource directories. As a professional, Bloom repeatedly encountered deep-rooted inefficiencies in how communities and their primary-service providers produced and shared information about services. His inquiries eventually led him to explore this “problem of the commons.”

The Ostrom Workshop, named for Elinor Ostrom, draws from the Nobel laureate’s groundbreaking research on how communities can successfully manage shared resources—often called “commons”—without centralized management. Through group-governance structures with clear frameworks, decentralized groups can sustainability manage common resources. Thinking about that problem and applying it to data, it’s easy to see how, without effective community governance, data can become unreliable, siloed, and redundant.

This problem is particularly tricky in smaller communities, but the problem is really a systemic one, as Bloom writes about in a December 2023 blog post that introduced a white paper sponsored by the Ostrom Workshop. Bloom chalks the resource-directory problem up to a lack of incentives for human-service providers to collaborate and share data—a phenomenon he calls the “resource directory anti-commons.”

As a practitioner, not an academic, Bloom began searching for practical solutions to this problem over a decade ago. Although academic literature on the “digital commons” exists, it is largely siloed in academia and university research. In other words, it’s not available—or at least not available in an accessible format—to communities themselves that can benefit from findings.  Bloom envisioned a common language—simple icons and terminology—for service providers and data intermediaries to apply data-governance frameworks in solving the digital-commons problem.

Bloom began engaging with the Ostrom Workshop in Bloomington in 2014 and five years later was invited to be a visiting scholar. Here was his opportunity to refine his vision of resource-directory information as a public good in line with Ostrom’s original theory of commons governance.

By 2023, Open Referral was prepared to engage communities with a practical tool kit. In partnership with the Midwest Big Data Innovation Hub’s Community Development and Engagement Program, Open Referral developed a participatory workbook and facilitated a pilot workshop to help communities eliminate redundancy and inefficiency in data collection. The intended users are information managers and their partners—those who do the work of data sharing and governance.

“Sometimes resources are more effectively shared as commons than privately managed—and this works best when the people who use those resources are also involved in the governance of the resources,” said Bloom. “That blending of user and producer is called co-production.”

The co-production approach paid off. Open Referral worked with a partner in Minnesota, Stratis Health, to facilitate a two-day pilot workshop in October 2024. Dozens of participants representing public, nonprofit, and for-profit organizations across the healthcare and human-service sectors worked with the Open Referral team to “draw” their own data-sharing plans. Partner organizations were challenged to answer core questions to data sharing, including Which agencies are involved with the same types of data? What services do they provide? Where are they located? When and how are they accessed? 

Pictured Left: Workshop participants with Greg Bloom (photo credit: Open Referral)

Pictured Right: Workshop participants take part in a system mapping exercise (photo credit: Open Referral)

Senka Hadzic is a Program Manager with Stratis Health, working on social determinants of health (SDOH) and opioid-overdose-prevention initiatives. Hadzic works with others at Stratis on a Shared Directory Infrastructure strategy, part of the organization’s larger initiative to improve social-needs referrals. 

“We first engaged with Greg Bloom [of] Open Referral in 2023 as a national subject matter expert on resource directories,” said Hadzic. “He helped convene a multisector work group of resource directories, health plans, health systems, and community organizations to craft an initial set of recommendations on how we as a state move toward the comprehensive and universally accessible resource directory infrastructure. That set of recommendations proposed a central coordinating role, data utility, or this shared infrastructure. The workshop held in 2024 was proposed to further flesh out what this could look like.”

Open Referral offers participants some shared terminology to describe the problem that they all experience in different ways. There are, of course, the actors that exist in any data-sharing framework: help seekers, service providers, data stewards, and referral providers. There are also key concepts to data governance: databases, service records, and resource data utilities. But perhaps most importantly, the Open Referral workbook invites participants to explore various institutional-design frameworks, ultimately choosing which best fits their own unique challenges and circumstances. 

Pictured: Status quo of ineffective and siloed resource-directory ecosystem. Source: Open Referral Community Resource Data Infrastructure Design Workbook

Pictured: Vision of a healthy resource-directory ecosystem. Source: Open Referral Community Resource Data Infrastructure Design Workbook

Data registers are official lists that are routinely monitored and verified for accuracy. A resource data utility is a designated provider of universally accessible, open data services within a specific domain that is often maintained for the good of the general public. Finally, a resource data collaborative is a group of organizations maintaining and collecting data together, resulting in higher quality and lower cost than if they had maintained a database independently.

Communities often benefit from more than one of these frameworks, with registers embedded in a resource data collective, for example. At the workshop, participants from similar service areas first drew their current data ecosystems. Then, they identified siloed areas and redrew an improved future state.

Each data-sharing ecosystem might look a little different; for instance, a group of individuals from organizations involved with food assistance (a directory of food assistance, 211, and a food pantry)  mapped out the landscape of local food-assistance providers in which a data utility maintains open-access data. Another group of community-based organizations (CBOs) relied more heavily on an open-data register. The exercise identified overlapping data collection in some cases and, in others, it even highlighted gaps in data.

“The tool kit is designed to empower groups of information intermediaries, particularly those doing the work of data management, along with their community partners who stand to mutually benefit from their work,” Bloom explained. “We want to provide clear guidance for designing collaborative conversations, asking productive questions about data governance and applying first principles without needing to learn all the jargon.”

Feedback from the Minnesota workshop was critical for the Open Referral team to iterate and improve on their workbook. By and large, the feedback from participants was positive. Said one participant, “[There were] productive and insightful conversations. [We discussed] creative solutions from different industry perspectives.” Participants in the Minnesota workshop consistently reported that the event enhanced their understanding of the resource-directory landscape in Minnesota and deepened their awareness of the challenges involved in managing resource data.

“While there are still outstanding questions that need to be addressed among the workshop participants, I am very pleased that we came out with specific outputs that we can act upon,” said Hadzic, of Stratis Health. “I also appreciated Greg’s approach to the design of this workshop by not only obtaining participant feedback before the workshop, but also taking into consideration the 2023 recommendations and our feedback as a convener on the needs of this community. His expertise and facilitation and the workshop provided us with the structure and outputs that we need in order to advance data utility in Minnesota.”

Bloom and his team are incorporating feedback to improve the tool kit, adding clearer prompts, expanding iconography, and refining examples of information flows. The workshop findings are outlined in a recent Open Referral blog post, and the workbook will be available online soon. Open Referral plans to bring this framework to more communities nationwide, addressing inefficiencies that impede service delivery.

Learn More/Get Involved:

Contact Greg Bloom if you are interested in hosting an Open Referral workshop in your own community.

Contact the Midwest Big Data Innovation Hub to learn more about other Community Development and Engagement projects we’ve supported. 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.

By Francie Fink

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.

As of 2020, almost a third of American households reported difficulty in paying energy bills, or were forced to keep their home at an uncomfortable and potentially unsafe temperature to save money. With increasing summer temperatures and more extreme winter temperatures anticipated in years to come, this statistic is likely to become only more alarming. Policymakers and researchers have developed a metric to standardize which homes pay more than others towards energy bills, as a proportion of their annual household income. That metric, called a household’s “energy burden” can be calculated and expressed as a simple percentage:

(Annual money spent on energy costs)/(Annual household income) * 100.

You might now easily calculate your own household’s energy burden. You might also easily see how this proportion can be alarming: for instance, for a household making $25,000 a year with $2,000 towards energy bills in that same year, that family’s energy burden is 8%. Common standard is that 6% energy burden or higher constitutes an energy-poor household, this being the average energy burden of a household between 0–80% area median income (AMI). A tricky characteristic of this calculation for policymakers hoping to intervene is that we often don’t have accurate, accessible data on household income. This component is key in accurately estimating household energy burden and is essential for effectively directing assistance to those who need it most.

Minnesota can experience bitterly cold winters and, thus, its households rely on dependable heating. Energy bills can rack up for low-income households, particularly for those heating with expensive fuels and inefficient equipment. In the Twin Cities, for households less than 30% AMI, the average household energy burden for Minneapolis is 10%—and for St. Paul, 7%. While incoming Inflation Reduction Act funding and existing utility programs provide an opportunity for energy-efficient upgrades and bill assistance, respectively, it’s currently very difficult for administrators to know which households can benefit most. If a family is seeking assistance through Minnesota’s Energy Assistance Program, as of now, they must first find that the program exists, then fill out a somewhat lengthy application with an income-verification step. Or, if program administrators aren’t able to reach target households, these households might instead engage in risky financial behavior, such as taking on loans to keep the heat on.

A small group of researchers at the University of Minnesota’s (UMN) Center for Sustainable Building Research partnered with the Midwest Big Data Innovation Hub (MBDH) to improve the methodology of estimating household income in an effort to enable proactive outreach to families experiencing high energy burden.

“Energy burden is often addressed as something that has to have already been experienced,” says Diba Malekpour Koupaei, Research Fellow at the Center for Sustainable Building Research. “We aim to be proactive by keeping an eye out for households that may currently be experiencing it or could face this challenge in the future. This approach has the potential to increase our capacity for outreach to those most in need of intervention.”

The team, led by Malekpour, aimed to develop a framework for estimating household income using what is called the House Price-to-Income Ratio. The metric is essentially exactly what it sounds like, and its main purpose is to gauge the affordability of a home for a given family. The UMN group realized they might be able to use this metric for something else: income estimation in the context of energy burden. The value of a home might just be a good predictor of its occupants’ income.

Researchers can and frequently do use microdata, or unidentifiable, individual-level data, from open sources like the U.S. Census’ American Community Survey (ACS). The ACS has information on income, home value, and energy costs for a sample of American homes, so it can be valuable for energy-burden studies. Previous research by the UMN and other groups couldn’t identify a correlation between household income and home value within the dataset. Building on work from another study, however, the UMN team was able to use a relationship between home value and income when matching up deciles of these two metrics.

The relationship between household income and home value wasn’t a strong enough predictor when analyzing individual data points. But when the entire distribution of home values was matched on a decile basis to the distribution of incomes, a significant relationship revealed itself. When both datasets are split into equal 10% parts, a linear regression model can be established for each matched pair of deciles. For example, the lowest 10% of home values are compared to the lowest 10% of incomes, and so on up to the highest deciles. This shows the relationship between household income and home value more effectively than traditional methods.

Through some trial and error, the UMN was able to use the decile-to-decile approach to establish a relationship that can be used across the country, not just in Minnesota. In practice, this relationship can be used to estimate income at the Census block level, when geomatched with local home assessment data. Using the 6% threshold for the amount of earnings a household can spend on energy costs before becoming overburdened, the research team was able to take their findings one step further. Solving for “amount of money spent on energy costs annually” in our original energy-burden equation under 6% energy burden and a given income, one can find the maximum amount of money a household is able to spend yearly before becoming overburdened. The graph below shows that, interestingly, different neighborhoods in Minneapolis have noticeably different annual energy budgets. See, for instance, that single-family homeowners in downtown and uptown communities can spend more on energy each year before being overburdened than the Powderhorn and Phillips communities. The same, though, might not be true for those in multifamily housing.

The MBDH supported Malekpour and her team’s research in 2024. The team’s work has resulted in a methodology manuscript currently in submission. The publication will come up in a lookup table and can be used anywhere as long as there is assessor data available. The assessor data will serve as a broadly available source for home value in determining the relationship to household income. The team hopes to make their methodology publicly available, potentially changing the game for energy-assistance and home-upgrade programs seeking out families vulnerable to high energy costs in relation to their earnings.

Also in the works is an interactive geographic information system (GIS) interface that uses the methodology to convey household energy budgets on a regional or even more granular scale. The interface would allow individuals to contribute their own income, home-value, and energy-cost data anonymously to hone the model. The UMN team hopes to recruit graduate students to incorporate this voluntary data in the near future.

Get Involved/Learn More

Learn more about the UMN Center for Sustainable Building Research here.

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, 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.

By Francie Fink

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.

South Bend, Indiana, is starting to see the effects of climate change. In both 2016 and 2018, the city experienced devastating flooding that inundated roads and low-lying areas. According to the 2023 South Bend Climate Risk and Vulnerability Assessment, extreme heat days have steadily been increasing—with the average number of days above 95 degrees Fahrenheit projected to increase by at least 5 and at most 50 by mid-century. Most recently, though, wildfire smoke from hundreds of miles away quite literally turned the sky a different color, setting an eerie backdrop for South Bend residents struggling with respiratory issues and concern for the future of the air they breathe. Wildfire smoke and its visible threat highlighted other concerns: vehicle emissions on hot, sunny days increasing ozone levels and industrial processes releasing harmful particulate matter.

The City of South Bend’s Department of Innovation and Technology and Office of Sustainability, whose missions involve improving residents’ access to technology and mobilizing residents to the climate emergency, became increasingly interested in initiating an environmental health campaign. The problem? City officials lacked real-time, hyperlocal data on air quality to inform public health interventions. Levels of primary pollutants, such as ozone and fine particulate matter, can vary substantially even within a city. This fact poses challenges for cities like South Bend, that rely on air quality readings from one state-owned regional environmental sensor. When identifying locations for cooling centers, for example, there are limited data to identify where extreme heat persists. Schools on one side of town might experience poorer air quality than those on the other on any given day and decide to postpone outdoor recess accordingly.

A new City campaign, called Sense South Bend, would accomplish three main goals:

• • increase the collection of high-quality environmental data;
• • inform the public on the availability of these data and actions to take during different air-quality levels;
• • inform local public health and climate change interventions.

Alex Bazán, South Bend’s Director of Sustainability, says of the initiative “SenseSB provides on-the-ground data that will allow the City to develop policies and programming that equitably serve community members. It has provided opportunities to engage with residents and community partners to discuss air quality, climate change, and how as a community we can work together to improve quality of life.”

To obtain 24-hour air-quality readings at the neighborhood level, the City of South Bend partnered with TELLUS Networked Sensor Solutions. TELLUS’ wireless environmental sensors, when deployed, can measure over nine pollutants and related metrics. Analysis of these long-term data on particulate matter, ozone, carbon monoxide, ambient temperature, and more will allow City of South Bend officials to determine priority geographies within city limits for public programming and infrastructure to address poor air quality and associated health concerns, such as asthma and heart disease. South Bend deployed 22 sensors on city-owned assets, across city limits, over the course of Spring 2024.

Perhaps most relevant to South Bend’s ultimate goal of providing easily digestible and high-quality air-quality readings to residents, however, is TELLUS’ AirView model, which reflects a real-time interpolation of sensors. The more sensors that are deployed, the better the interpolation. The end result is a color-coded map of city air quality, ranging from healthy to hazardous.

Once South Bend obtained more accurate, geographically focused data, they needed a plan to make air-quality data accessible to the public. They also wanted accompanying guidance on actions to take during air-quality emergencies. Which groups are particularly vulnerable to poor air quality? What are easy actions to reduce air pollution? Are there thresholds for joining in outdoor activities during poor air-quality events? These remained complex questions with ambiguous answers.

The City of South Bend partnered with the Midwest Big Data Innovation Hub (MBDH) through its Community Development and Engagement Program to host a Graduate Environmental Health Fellow, who, over the course of the Spring 2024 Semester, gained learning experience in research, community engagement, and science communication while helping to build out the City of South Bend’s environmental sensing initiative, aptly named Sense South Bend: Air Quality.

Francie Fink, a Master of Public Affairs candidate at the University of Wisconsin–Madison concentrating in Energy Analysis and Policy, was onboarded as the City’s Environmental Health Fellow. From January through May 2024, she conducted research that ultimately informed the creation of a public-facing webpage and accompanying knowledge-based article, social media education campaign for air quality, and supplemental outreach materials for the Sense South Bend: Air Quality initiative.

“Working with the City of South Bend in this role was an incredible experience,” said Fink, “In March, I presented on Sense South Bend to the city’s Environmental Research Coalition, a group formed to strengthen the connection between community-based scientific research and local government. They were interested in how my research complemented ongoing City efforts.”

The MBDH also supported the professional development of Barbara Dale, Project Manager in South Bend’s Office of Sustainability. Barbara attended the Health Effects Institute’s Spring Conference and brought back important insights, which were incorporated into City messaging around air quality. An important one? Often, groups most vulnerable to poor air quality, such as communities living near highways and outdoor workers, don’t necessarily consider themselves sensitive.

Pictured Left: Francie Fink, Environmental Health Fellow, tables for Sense South Bend at South Bend area’s Bike to Work Week in May 2024.
Pictured Right: Barbara Dale, Project Manager in South Bend’s Office of Sustainability, attends and represents South Bend at the Health Effect Institute’s Spring Conference in Philadelphia in April 2024.

The initiative’s webpage hosts the AirView map with the Environmental Health Fellow’s findings and recommended guidance based on the following air-quality levels: good to moderate, unhealthy, very unhealthy, and hazardous. The guidance outlines sensitive groups and checks on physical activity. For instance, for residents in orange zones on the map, the air quality is unhealthy and sensitive groups, such as those with heart/lung disease and pregnant women, should make outdoor activities short and easy, monitoring symptoms for shortness of breath and heart palpitations.

Sense South Bend: Air Quality will lay the foundation for additional environmental sensing initiatives in South Bend, like Sense South Bend: Water Quality and Sense South Bend: Mobility. Already, residents have interacted with the webpage and social media posts, sharing notices of days with poor air quality and engaging in discussion around the sources of air pollution. Some residents have even expressed interest in purchasing their own TELLUS air sensor, to help improve the network of publicly available sensors.

“As climate change intensifies the challenges of poor air quality and severe heat, real-time data from sensors across the community will help us to better serve our residents,” says Patrick McGuire, Technology Equity Manager for the City of South Bend. “We can empower residents to take informed precautions for their health and drive data-driven solutions for a more resilient city.”

Get Involved/Learn More

To learn more about the Sense South Bend: Air Quality initiative, visit https://southbendin.gov/air-quality/. For more information on the Air Quality Index and related health concerns, visit AirNow.gov at https://www.airnow.gov/air-quality-and-health/. If you are interested in contributing to the network of TELLUS environmental sensors by deploying your own device and making it publicly available, visit https://www.tellusensors.com/products/.

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, 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.

By Francie Fink

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.

For many Midwesterners, the impacts of climate change can feel distant, especially when compared to the more immediate threats faced by coastal regions. While Ohio may not experience the intensity of hurricanes in the Gulf, the future promises challenges like extreme heat and increased precipitation. Understanding these subtle, long-term effects often requires a closer look at data and long-term trends. And while you might not own a farming operation, your neighbors several miles south might. You wouldn’t have a way to know until seeing for yourself the trends in agricultural production over the past several decades.

Midstory, a Midwest nonprofit specializing in multimedia storytelling and research, set out to unpack trends and data addressing climate change for Ohio’s residents. The Midstory team is made up of data analysts, storytellers, and multimedia experts, all who know how to effectively communicate scientific information. Their portfolio of multimedia projects includes digital series and stories on everything from the local music scene to agriculture and homesteading in Ohio, and everything in between. They became interested in telling the story of Ohio’s changing climate in an effort to surface the gaps in information Ohio’s residents have on topics that everyone cares about, such as agriculture and air quality. Midstory embarked on a new initiative, Colors of Climate Change, to bring Ohio to the table in conversations around climate change.

Ohio’s diverse landscape is shaped by both its rural and urban populations. Home to 75,000 farms across 14 million acres and six cities with populations over 100,000, the state embodies a unique blend of lifestyles. This dynamic creates various social, political, and economic divides.

“We thought, how do we make the science or economics of climate change accessible to people? Not just accessible, but engaging,” Ruth Chang, creative director at Midstory, said.

To do this, they gathered quantitative data from various sources, including The University of Toledo and Bowling Green State University, alongside qualitative insights from interviews with policymakers, scientists, and farmers. This collaboration culminated in a permanent interactive digital series and a complementary data arts exhibit at the Toledo Lucas County Public Library.

The Midwest Big Data Innovation Hub (MBDH) partnered with Midstory to support program staff, fellows, and interns in the development of a six-part data storytelling series that explores, visualizes, and raises awareness of the current state of climate change in Ohio. The series, which included visualizations, audio episodes, and interactive maps, was a practice for Midstory in engaging with the public through a virtual medium. The team intentionally addressed six topics: (1) Ohio’s role in national climate conversations, (2) extreme weather, (3) public health, (4) agriculture, (5) economics, and (6) biodiversity.

Pictured: [Left] Concept Board for the Colors of Climate Change exhibit. QR codes displayed on the physical board directed visitors to additional information and graphics online. [Right] Exhibit displayed in the Toledo Lucas County Public Library gallery. Images courtesy of Midstory.

Data can be intimidating. In its raw form, it might contain hundreds of rows of information on a single topic: say, crop yield for corn, across tens of producers, for decades. Poring over these data, even in summarized form, can be tricky, and creating a cohesive narrative from it is even trickier. Marin Warshay, Editorial Fellow with Midstory, led the writing on this ambitious project and interviewed almost 50 individuals.

“There’s always this issue of explaining what you have learned, telling other people about it . . . but not many people teach you how to do that. I’m so grateful to have the opportunity to have honed that skill. It’s been challenging but rewarding to put my own opinions aside and craft explainer-style stories from the data,” said Warshay of her involvement with Colors of Climate Change. Warshay went on to explain that while words matter, an important takeaway is that the science was already there: “The story was a way to explain the data, but the data can stand alone.”

From there, the Midstory team took on a new challenge: how to make the information viewable from a two-foot distance, accessible to all age groups and all levels of digital literacy. In Ohio, the effects of climate change will be felt disproportionately by marginalized and underserved communities. As part of Midstory’s online narrative outlines, for example, historically redlined communities in and around downtown Columbus will experience extreme heat more severely than surrounding areas. A key objective of the multipart project was to make the information available to all Ohioans. Even the location of the physical exhibit, the Main branch of Toledo’s library system, was intentionally selected to maximize accessibility.

The library exhibit, which ran from July to August 2024, was Midstory’s most extensive physical storytelling project to date. The Midstory team envisioned a space where art and science coalesced, transforming complex data into interactive experiences that drew in visitors from all demographics. The resulting exhibit exceeded the expectations of the Midstory team and project stakeholders alike. Visitors could engage with immersive installations, hands-on displays, and visual narratives. In one section of the exhibit, visitors heard a crack of thunder as they read about the increased frequency of storms expected in Ohio. In total, the exhibit featured over thirty 4′ × 8′ colorful boards that presented data, allowing guests to explore the impacts of climate change on agriculture, local ecosystems, water quality and availability, and public health. The exhibit fostered organic conversations among diverse groups, from students to farmers, creating a shared understanding of the critical issues at hand.

You can explore a 3D tour of the exhibit here.

“While media coverage often sparks nationwide conversations about climate change, we sometimes overlook how it directly impacts our local communities. When you walk into the exhibit, Ohio is the center of the story,” said Logan Sander, editorial director at Midstory.

On July 27, 2024, Midstory hosted a 200-person reception called “Climate In Context,” with a panel, community tabling session, structured time for exhibit interaction, and keynote speaker, featuring Pam Dempsey, program director of the Data-Driven Reporting Project at the Northwestern University Knight Lab.

The digital series and exhibit received high praise from community members and local organizations. The Colors of Climate Change digital content has reached nearly 50,000 individuals, and almost 2,000 individuals have interacted with the physical exhibit. Midstory is excited to continue the project with support from their local community foundation. The additional funding will allow them to create and produce two additional episodes in their digital series.

Learn More/Get Involved

Explore Midstory’s Colors of Climate Change digital series here. Learn more about Midstory’s other multimedia projects here.

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, 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.