Predictive Cities: Leveraging New Data and Methods to Improve Urban Quality of Life

March 2017

Urban science is undergoing a transformation: new data sources, often collected in real-time, have made analysis of cities easier and more exciting than ever before. Digital exhaust, sensor data, and open government records allow for broader understandings of the impact of policy, as well as rapid advances in predictive analytics. Now, city governments need tools and techniques to help them leverage their limited human capital and infrastructure for data analysis. Meanwhile, private researchers are increasingly looking for ways to work on city-scale problems. This Radcliffe exploratory seminar develops tools for making big data useful to cities in efficient and scalable ways. Throughout, we encourage approaches that make the use of data in cities more open, and create a partnership between cities and their citizens. We seek in particular to spark collaborations between researchers and practitioners that will lead to what we call “research products”—research findings that can be translated into products that partner cities can use to improve quality of life. Thus, the program brings academic experts in urban economics, sociology, and data science together with city officials and technologists. In addition to new research products, it will develop an articulation of how data and predictive technologies can inform city governance, and launch a lean research group focusing on product-oriented urban data research and implementation. 

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