Data is just like real estate – it benefits greatly from location. When you associate an address or coordinates with a data point, it becomes spatial data, opening up new possibilities and challenges for analysis. With the right approaches and tools, spatial data scientists can track the spread of a disease, study the impact of COVID-19 on households, or assess environmental health across neighborhoods – offering rich new insights for policymakers, communities, and other stakeholders.
The Open Spatial Lab (OSL), a collaboration of the Data Science Institute and the Center for Spatial Data Science, is a new hub for the tools and partnerships essential for maximizing the potential of these approaches. In its inaugural year, the OSL, led by Dylan Halpern and Susan Paykin, will work with community partners in Chicago and across the United States to understand their data science needs and activate their spatial data for community and policy decision support. It also develops open source tools, projects, and resources that can be shared among researchers and organizations working in the spatial data science space.
For the lab’s founding philosophy, Halpern and Paykin chose a quote from legendary designers Charles and Ray Eames: “The best for the most for the least.”
“We’re focused on making these methods, tools, and applications more accessible to broader audiences,” said Paykin, the program lead for Open Spatial Lab. “How do you create something that is the highest quality, for the most people or different types of communities, for the least technical work required and the least amount of money required to fund it? We see a real opportunity to build on a lot of great open source software development in this field and reduce the on-ramp for social impact organizations to use spatial data science.”
The OSL is funded in its inaugural year by the Robert Wood Johnson Foundation, with the charge of building data capacity for organizations with a social or civic impact mission, while also creating broad analytic tools, dashboards, and other applications that can be shared among smaller organizations.
“The hub will be an evolving database of a lot of different aspects of spatial data science, with the hope that it helps projects have a second life and be more discoverable,” said Halpern, technical lead at Open Spatial Lab. “We’re interested in making the tools themselves more accessible to wider perspectives, to folks coming from different areas of data science and data-related programs from the community, and trying to open up the field of who can engage directly with these processes. We’re also thinking about how these tools can be thoughtfully put together so that they’re cheap or free to own long term, and something that organizations can manage and doesn’t have to be this huge burden moving forward.”
In addition to the hub, Open Spatial Lab will work directly with organizations who have projects that could benefit from spatial data science. Through their Robert Wood Johnson Foundation grant, they’ll connect with partners in the public health, health equity, and racial equity space. Locally, OSL will plug in with efforts such as the South Side Civic Scopeathon to find Chicago community groups that work with spatial data.
“What works really well with our approach is when there’s some sort of place-based or spatial component, which many of these projects have because they are by nature interested in outcomes in different neighborhoods, or how land is developed within a city in a racially equitable way, or ensuring different health outcomes are equitable across cities,” Paykin said. “We’re looking for groups that are interested in producing public-facing data tools or outputs that reflect an expanded data capacity for their organization in terms of collecting, working or visualizing data.”
As part of the Data Science Institute, OSL will also have the opportunity to contribute to interdisciplinary projects with social impact in Summer Lab, the 11th Hour Project Hub, and the DSI Community Data Fellowsprogram.
“There’s a really good opportunity for us to engage with those projects and learn and understand these different perspectives, use cases, or needs,” Halpern said. “DSI created a clear connection between data science at the University and public impact, and that’s what we were really excited about joining.”