By Rob Mitchum // February 21, 2014
The future of cities doesn’t fit easily within disciplinary boundaries. Traditionally, urban research has been the domain of social scientists, while architects, urban planners, and policymakers implement academic findings into real practice. But the rising availability of city data and the computation to model and simulate the complexity of cities brings new scientists and partners into the mix, opening up new possibilities for understanding, managing and building cities.
For the AAAS 2014 session, “A New Era for Urban Research: Open Data and Big Computation,” CI Senior Fellow and Urban Center for Computation and Data director Charlie Catlettassembled an “all-star cast” of social scientists, computer scientists, and representatives from government and industry to illustrate these new partnerships. The urgency driving the presentations and discussions was the rapidly growing urbanization around the world, particularly in China, where they will need to build the equivalent of one New York City every year to house its growing urban population, Catlett said. In the face of these imposing statistics, speakers demonstrated exciting new work going on in Chicago, New York, Beijing, and Boston.
The first two speakers shared an interesting research instrument in common: taxis. Steve Koonin of the NYU Center for Urban Science and Progress and Eric Chang of Microsoft Research Asia presented how they are collecting new kinds of data from hundreds of millions of cab rides in New York City and Beijing to measure “the pulse of the city” — everything from traffic to economic behavior to the influence of weather. Both centers are also developing new ways to collect data from the city, including a CUSP project using cameras to measure heat and light from thousands of NYC buildings simultaneously, and a Microsoft project estimating hyper-local evels of air pollution in Beijing neighborhoods.
While these studies and partnerships with government agencies are starting to help researchers to fill the gaps in our knowledge about a city’s dynamics, there’s much more work to be done in opening up and sharing valuable information, Koonin said.
“One of the major challenges in this field is getting access to the data,” Koonin said. “Everybody hoards the data. Government agencies hoard the data because data is turf and power. The academics hoard the data because that’s how you get a publication. And companies hoard the data because it’s a differential business advantage. So breaching those silos is a difficult but important task.”
But just collecting more and more data is not enough to understand cities and produce change, reminded Mario Small, Dean of the Social Sciences Division at the University of Chicago. Small’s research looks at the relationship between population and organizational density — the concentration of businesses and services in a neighborhood — and poverty. To illustrate the need to go beyond surface statistics, Small compared two neighborhoods with similar levels of poverty: Chicago’s Woodlawn, and New York City’s Central Harlem. Looking just at the economics, a researcher might think these communities were very similar. But anyone walking around the two areas would immediately see vastly denser population and many more stores, restaurants, and gathering places in Central Harlem than in Woodlawn.
In fact, a comparison of Woodlawn with over 300 American cities finds that it is on the extreme end of sparse population and lack of services, Small said, a situation that may relate to higher levels of violence in the community. Importantly, while data helped contextualize Woodlawn’s neighborhood characteristics, the original hypothesis came from old-fashioned footwork and traditional social science methods.
“In order to develop social science theory that’s going to tell you what questions to ask and what data to look for and what data to integrate, what you actually need is the opposite of big data: to go all the way down to the ground and do micro-level data,” Small said.
In Boston, that means going beyond an impressive dataset of over 300,000 city service requests to examine the street-level disorder of neighborhoods, said Daniel O’Brien, research director of the Boston Area Research Initiative. BARI is led by Robert Sampson, a former UChicago sociologist famous for his work on the influence of neighborhood characteristics upon outcomes such as health, violence, and poverty. While Sampson couldn’t make the panel due to snowy weather on the East Coast, O’Brien gave an overview of BARI’s efforts to study the ecometrics of Boston with a combination of surveys, streetwork, sensors, and city data.
By comparing calls to Boston’s city services hotline with field observations, the BARI team could estimate the frequency of problems such as trash, graffiti, housing issues, and neglect as well as civic responsiveness — the likelihood that a problem in a given neighborhood would be reported to the city. That can help researchers collect more accurate and micro-scale information about the city, monitoring neighborhood conditions and helping guide city services more efficiently.
Yet in order for urban data and research to make meaningful impact, government and industry partners must buy in to the strategy as well. Brenna Berman, Chief Information Officer for the City of Chicago, explained how the administration of Mayor Rahm Emanuel prioritizes open city data and collaborations with academic researchers and “civic hacking” volunteers. From building an analytics platform built to monitor city operations during the 2012 NATO summit to using 311 data and machine learning to predict rodent problems in neighborhoods before the first rat is spotted, Chicago is bringing advanced data science into City Hall.
“We have leadership from the top on this,” Berman said. “The mayor made it very clear from the beginning of his administration that data was going to be the hallmark of everything he did — he makes his decisions based on data and he expects the leaders in his departments to do the same. He views big data and analytics as the key for every department to make the most of the limited resources that we have.”
Chicago-based architecture firm Skidmore, Owings, & Merrill is known for building some of the world’s tallest buildings. But Philip Enquist, Partner in Charge of Urban Design & Planning at SOM, demonstrated how the firm is using data to look beyond skyscrapers and generate new perspectives on the use of land and natural resources in cities and beyond. On the building scale, SOM is exploring unorthodox materials, such as wood and “green walls,” and using weather data to build more energy-efficient skyscrapers. For broader context, the firm is looking at “urbanized corridors” in the US and abroad, Enquist said, thinking about how to design new cities that encourage efficient urban living with minimal disruption to natural resources.
Those two threads come together in SOM’s design for the Chicago Lakeside Development, a 600-acre residential and commercial property on the South Side site of a closed U.S. Steel Plant. Designers are working with researchers at the CI’s Urban Center for Computation and Data to treat Lakeside as an experimental site for the next generation of large-scale city infrastructure, with reduced energy consumption, improved water conservation, and better integration with the adjacent Lake Michigan. If successful, Lakeside will not only be a vibrant new Chicago neighborhood, but also a model for similar and even larger developments springing up around the world.
“There’s a lot riding on cities. The demand for new buildings and infrastructure is unprecedented,” Enquist said. “So this presents an opportunity to get it more right than we’ve been getting it, and data plays a very big role in that.”