The new Center for Spatial Data Science joins the Computation Institute and the Social Services Division, bringing advanced spatial analytics methods to fields ranging from economics and urban sociology to medicine and public health. Learn about the center's research collaborations and initiatives in software, training, and developing new methods.
Last year, in an ornate downtown Chicago ballroom, the seeds were planted for a new multidisciplinary research network with an ambitious purpose: to understand and improve cities. By mixing together experts in computer science, public health, education, architecture, urban planning, art and social science, the Urban Sciences Research Coordination Network (USRCN) hoped to create versatile and knowledgeable teams that could find new approaches to study cities in a rapidly urbanizing world. Sixteen months later, the early fruits of those new collaborations helped inspire a new wave of discipline-crossing partnerships at the 2nd USRCN meeting, organized by the Urban Center for Computation and Data and held inside the world famous Art Institute of Chicago.
Through civic hacking events and open data portals, the Obama administration has embraced the potential of data and programming to improve the performance of government for its citizens. As academia and industry increasingly moves toward using computational techniques to inform policy decisions, these more ambitious efforts have also attracted the attention of the White House. On April 4th, the President's Council of Advisors on Science and Technology (PCAST) convened a panel called “Analytical Techniques to Improve Public Policy Decision-Making” at their regular meeting, inviting CI Senior Fellow Charlie Catlett and three other experts to report on the promise of this young research area.
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 Catlett assembled an “all-star cast” of social scientists, computer scientists, and representatives from government and industry to illustrate these new partnerships.
Newspapers don't always have the most exciting afterlife. A day or two after printing, most newspapers retire to a secondary role as kindling for the fireplace, stuffing for fragile items or a disposable surface for house-training pets. But the content of newspaper articles can have value long after publication for researchers interested in the daily, local pulse of a particular subject. Traditionally, information was extracted from old newspaper clippings by arduously crawling through endless microfiche files or (more recently) web pages. But new methods for text mining offer a fast, automated way to turn old newspaper articles into valuable information — which can then be poured into even more ambitious project.
Those methods were the backbone of a talk at the Computation Institute by John T. Murphy of the CI and Argonne National Laboratory's Decision and Information Sciences Division. An anthropologist, Murphy is interested in the ways that towns in the American west handle water management — a utility that many of us take for granted, but which can be a bitter political battlefield. To sum up these disputes, Murphy referenced a quote often attributed, albeit probably falsely, to Mark Twain: "Whiskey is for drinking, water is for fighting over."
A large chunk of a government's budget can be traced back to a small number of frequently used, expensive programs. These can include the costs of adult and juvenile incarceration, foster care for endangered children, or safety net services such as treatment for mental health or substance abuse for poor individuals. These programs don't operate in isolation; many individuals or families in one of the above programs will also be in at least one more at some point in their lives. Finding these social service "hotspots" could allow governments to more effectively distribute resources, reducing costs without sacrificing services at a time when budgets are especially tight.
But the data from each of these programs are walled off in different departments, such as the Departments of Corrections or Children and Family Services, with limited to no sharing across bureaucratic lines. In his Sept. 27 talk at the Computation Institute, Robert Goerge, a CI senior fellow and senior research fellow at the University of Chicago's Chapin Hall, described how integrating these silos of public sector data can inform more efficient government spending, and how computation can help.