Organized by the Urban Center for Computation and Data is the Urban Sciences Research Coordination Network (USRCN), a group funded by the National Science Foundation. The USRCN will leverage a unique and growing collection of data sets and research teams spanning The University of Chicago, the School of the Art Institute of Chicago, the City of Chicago, and Skidmore, Owings & Merrill, a global architecture firm designing city-scale urban infrastructure.
Global urbanization raises challenges and opportunities related to density and scale in areas including transportation, food production and distribution, human health and wellbeing, education, social policy and services, and management of water and energy. The accelerated creation of city-scale developments and regional megalopolises brings urgency to understanding their impact on the local and regional environment and inhabitants. Guided by sparse, often stale data, qualitative studies, and intuition and experience at smaller, 20th-century scales, current city design, planning, and operation approaches often produce unanticipated, far-reaching consequences that do not manifest until their effects are difficult, or impractical, to unravel.
Advanced computational and information capabilities, along with unprecedented and growing volumes of relevant data, suggest new opportunities to understand the state of urban social and economic systems. These methods also allow researchers to develop calibrated, validated computational models to explore the potential impact of new policies, investments, and accelerating expansion of urban built infrastructure.
New insights and more effective policy and planning are possible if research teams explore these data as an integrated corpus. Yet the equilibrium state is one of daunting fragmentation and access restrictions that can only be overcome by a critical mass of researchers and a compelling, broad research agenda that resonates with the near- and long-term challenges of policymakers and citizens. Moreover, new data organization and analysis approaches will require partnerships between social, behavioral, education, and economics scientists and computational scientists.
The USRCN brings these communities together to develop an integrated research agenda for an interdisciplinary, data-driven approach to urban research, analysis, and planning, exploring and prototyping methods, processes, tools, and infrastructure necessary to support such science. Participants include: