For the past four years, the Data Science for Social Good summer fellowship has brought over 160 fellows from around the world to Chicago to work on data-driven projects with real world significance. They've used machine learning and predictive analytics to improve graduation rates, anticipate urban blight and water infrastructure issues, direct hazardous waste inspections, deliver targeted social services, and much more. Now, the program, run by the CI's Center for Data Science and Public Policy, is looking for fellows, mentors, project managers, partners, and funders for 2017, with applications due at the end of January.


Social science and public policy have always been connected, to varying degrees of success. In an ideal world, understanding the mechanisms behind social processes -- both good and bad -- would directly inform the creation of policies that promote social benefits and reduce consequences. But language, whether academic or political, often separates the two disciplines.


The newly launched National Center for Opportunity Engineering & Analysis (NCOEA) at the Computation Institute will use the latest computation and data science tools to help close the skills gap, reduce economic inequality, and provide new ways to search for training connected to employment and career opportunities.


Urban Center for Computation and Data

The Urban Center for Computation and Data unites scientists from the University of Chicago and Argonne National Laboratory with educators, architects and government officials to capitalize upon the growing availability of city datasets and the emergence of urban sensor networks. The interdisciplinary collaboration will analyze and integrate those data sources and build complex computer models that can anticipate the impact of policy decisions, investments, urban development or other interventions on a city and its residents.

Knowledge Lab logo

Knowledge does not arise from the simple accumulation of facts. Rather, it is a complex, dynamic system, and its emergent outcomes - including scientific consensus - are unpredictable. The complexity of knowledge creation has exploded with the growing number of participating scientists and citizens. If human knowledge is to grow efficiently, we need a deeper understanding of the processes by which knowledge is conceived, validated, shared and reinforced. We need to understand the limits of knowledge in relation to these processes. In short, we need knowledge about knowledge.

The National Center for Opportunity Engineering & Analysis, NCEOA, will create a new field of applied data engineering and analysis with the goal of providing new tools, open services and a research platform. These efforts will increase access to opportunities for all Americans in the job markets, education attainment, career training, and the utilization of support services.  

Researcher Spotlight