Cities are traditionally built from the pavement of streets and roads, the glass and steel of skyscrapers, the trees and grass of parks and public spaces. But increasingly a new material is used for the construction and management of cities: data. The growing torrent of information that city governments release and researchers collect is connecting with new tools developed by computer scientists, enabling significant advances in urban planning, medicine, social science and other spheres.
On Nov. 20, representatives of those fields gathered onstage for Chicago: City of Big Data, a UChicago Discovery Series panel discussion of research and educational efforts focused on transforming cities through data and computation. In a vibrant 90-minute conversation moderated by Charlie Catlett, director of the Urban Center for Computation and Data, the panelists described work underway at the University of Chicago and Argonne National Laboratory and outlined their visions for the future of data-driven urban design and governance.
The drive to create smarter cities is not just a local concern, but a global challenge. In his introduction, Computation Institute Director Ian Foster pointed out that half of the Earth’s population currently lives in cities—a portion that will rise to 70 percent by the year 2050.
“I think it’s no exaggeration to say that the health and prosperity of humanity during this next century will depend very much on how effectively we are able to run, design and hopefully improve the cities in which we live,” Foster said.
But the panelists agreed that Chicago is currently a leader in developing new data-driven approaches to urban challenges. Since his inauguration in 2011, Chicago Mayor Rahm Emanuel has emphasized the public release of city data and its use to direct policy and operations. As Chief Data Officer for the city for the first two years of Emanuel’s term, panelist Brett Goldstein oversaw the implementation of those efforts, including the creation of the City of Chicago Data Portal.
Goldstein discussed a project in which the city of Chicago studied the relationships between different types of 311 calls—in this case, calls about rats or broken or missing garbage cans. In some neighborhoods, an increase in calls about garbage can problems was found to predict a later increase in rodent infestation calls, which led the city to intervene earlier when the first groups of calls spiked.
“If you envision the model of the future, we as government and we as the community are able to provide these inputs and sensors, and we can start to do things smarter,” said Goldstein, now the inaugural fellow in Urban Science at the Harris School of Public Policy. “Instead of chasing our tails and being reactive, we can start preventing.”
But data can do more than boost the performance of city services, said panelist Rayid Ghani, research director at UrbanCCD and senior fellow at the Harris School. To realize its full potential, a new generation of data scientists interested in programming, statistics and other computational skills need to be motivated to work on projects with social impact.
“Chicago’s just an example of what we can do, but hopefully we can make it a much broader thing where the first thing people think about data, it’s not finance, it’s not search, it’s not social networks, it’s community development and health care and education,” said Ghani, who was chief scientist of the Obama for America Analytics team and now leads the Eric & Wendy Schmidt Data Science for Social Good Summer Fellowship.
While statistics and modeling have long been used to make forecasts, the true data challenge today has moved from predicting the future to using data to influence behavior in positive ways, he said.
“The useful part is not the prediction, the useful part is how do I change that behavior,” Ghani said. “If you are at risk of some sort of disease, I can predict it and watch you suffer through that disease, but that’s not very useful. It’s how you take action and how you influence this person to change their behavior, that’s where the real power is, and I think that’s where we’re moving towards.”
Better data, better health
One active example of using data to promote healthy behavior was provided by Stacy Tessler Lindau, whose MAPSCorps program employs South Side youth to go block by block and catalog assets—such as gyms, grocery stores and clinics—in South Side neighborhoods. Lindau said that the data the students collect is 30 to 40 percent better than what can be found on Google—an example of fixing community data’s “unvisibility.”
“The unvisible means the things we can’t see because of the social, psychological, emotional and prejudicial barriers that prevent us from seeing,” said Lindau, Associate Professor of Obstetrics/Gynecology and Medicine-Geriatrics at University of Chicago Medicine.
The data collected by MAPSCorps is then shared with the community through websites such as southsidehealth.org and incorporated into prescriptions given by doctors to patients through Lindau’s CommunityRx project.
“We put the unvisible on the map, and now we’re able to connect that information up to real people so they can use it to better manage their health,” Lindau said.
In an even more ambitious example of building new city infrastructure with data, the panel discussed the Chicago Lakeside Development, a 600-acre area on the former site of the U.S. Steel plant on Chicago’s South Side. The incredible scale of Lakeside—the size of the Loop and three-quarters the size of Central Park, Catlett said—offers both a computational challenge to architects and planners and an opportunity to see “social science in action.”
“It’s incredibly exciting to think about where buildings are placed, or where transportation and commerce exists so that we facilitate social interaction and track how that changes this community over time,” said Kathleen Cagney, associate professor of sociology and health studies at UChicago and director of the Population Research Center.
Cagney is launching an ambitious project to collect data on the neighborhoods surrounding the Lakeside site to monitor the impact of the development on the South Side. That data can also be incorporated into LakeSim, a collaboration between UChicago and Argonne scientists with Lakeside developer McCaffrey Interests and architect Skidmore Owings & Merrill to create a computational prototype for modeling the site’s design across multiple dimensions.
“If we can pull that data in, the first thing we can do is validate design decisions about a site in terms of the long-term impact on energy, climate, water and transportation,” Catlett said. “Then, we can feed those answers back and actually optimize the design of that site, optimize the architecture based on the outcomes that you want to see.”
Adapted from a story first posted by the Computation Institute; see the original here.