CyberTraining: CIU: Preparing the Public Sector Research Workforce to Impact Communities through Data Science
The ability to share data among researchers, citizens, government agencies, and educators creates potential for new research collaborations with significant real-world impact. However, cities are often unprepared to use cyberinfrastructure to support research that would impact their citizens and communities, and researchers often do not have access to or awareness of the kinds of data and questions that are relevant for communities. This project develops innovative and scalable instructional materials, for both in-person and online courses, to increase data science literacy to meet the public sector's emerging needs for experts in computational and data science. The materials emphasize the types of data necessary for communities to make informed decisions (e.g., administrative data on land use, constituent service requests, and crime statistics) and applies them to pressing issues presented by community partners, providing a real-world context for learning. The project leverages the University of Michigan School of Information's Citizen Interaction Design program and the Summer Program in Quantitative Methods of Social Research at the Inter-university Consortium for Political and Social Research (ICPSR) to train undergraduate students, graduate students, and public sector researchers in collecting, extracting, cleaning, annotating, and analyzing data generated and used by government organizations.
Principal Investigator: Libby Hemphill
Co-investigators: Cliff Lampe, Lynette Hoelter, Chris Brooks