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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.

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.

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.  

A joint initiative of the Division of Social Sciences and the Computation Institute, the Center for Spatial Data Science (CSDS) develops state-of-the-art methods for geospatial analysis, spatial econometrics, and geo-visualization; implements them through open source software tools; applies them to policy-relevant research in the social sciences; and disseminates them through training and support to a growing worldwide community of over 200,000 spatial analysts. The CSDS succeeds the GeoDa Center for Geospatial Analysis and Computation at Arizona State University. 

A collaboration between the Harris School of Public Policy and the Computation Institute, the Center for Data Science and Public Policy brings together data science and public policy experts. Its mission is to conduct research and create computational and data-driven solutions to large-scale social problems in areas such as healthcare, education, sustainability, and community development.

The Center's goals include:

Founded in 1982 as a result of a collaboration between the French government and the University of Chicago, the ARTFL Project is a consortium-based service that provides its members with access to North America's largest collection of digitized French resources. Along with ARTFL's flagship database ARTFL-FRANTEXT, ARTFL members are also given access to a large variety of other Subscriber Databases.

The Eric & Wendy Schmidt Data Science for Social Good fellowship is a University of Chicago summer program for aspiring data scientists to work on data mining, machine learning, big data, and data science projects with social impact. Working closely with governments and nonprofits, fellows take on real-world problems in education, health, energy, transportation, and more. For three months in Chicago they apply their coding and analytics skills, collaborate in a fast-paced atmosphere, and learn from mentors coming from industry, academia, and the Obama campaign.

The Hack Arts Lab (HAL) provides an open-access laboratory for creative digital fabrication and visualization.  Thismakerspace-styled workshop is designed to support a breadth of activity ranging from undergraduate projects to faculty-led exploration.  

HAL resources include 3D printers, laser cutter, advanced graphics, and microcontroller workbenches, all offered at minimal cost.