Grant: NSF PInet Poli-Informatics

BCC-SBE: PI-NET: Poli-Informatics Research Coordination Network

NSF Award #1243917

The grant establishes a Research Coordination Network (NSF 11-531)  to develop  a computational approach to political science and policy. The proposed RCN will cover a three year period and create a network of computer scientists, information scientists, social scientists, and political scientists. The goal of the project is to provide computational scientists opportunities to work with complex natural data and to expand data-rich analysis into mainstream political science research.

Granting Agency: National Science Foundation – Directorate for Social, Behavioral & Economic Sciences (SBE) – Social and Economic Sciences (SES) Division – Political Science Program. Building Community and Capacity for Data-Intensive Research in the Social, Behavioral, and Economic Sciences (BCC-SBE) http://www.nsf.gov/awardsearch/showAward?AWD_ID=1243917

Total Award: $498,355.00
John Wilkerson PI (Principal Investigator) University of Washington

 GMU Subaward: $143,592.36
Anne L. Washington Co-PI (Co-Principal Investigator) George Mason University

Abstract: This Research Collaborative Network (RCN) advances the new interdisciplinary field of PoliInformatics. PoliInformatics brings informatics to political research by promoting the analysis of very large and unstructured government datasets. The central objective of the RCN is to encourage scholars representing diverse disciplines such as computer science, information science, electrical engineering, statistics and computational linguistics to collaborate and apply their skills to the analysis of U.S. government activity. Over a three year period, the RCN will establish a new interdisciplinary scholarly network; conduct research competitions and workshops; train the next generation of PoliInformatics researchers; and produce a compendium of papers demonstrating the importance of this new field.
Large government data sets inspire previously unimagined research questions, analytic methods, and technology tools. The RCN will lead to valuable innovations in how government activities such as lawmaking, budgeting and policy implementation are studied and understood. It will encourage highly capable scholars possessing diverse research perspectives to focus their attention on important technical and substantive challenges presented by rapidly expanding repositories of government data. The infrastructure that these researchers develop to address these challenges will then be available for use by others–students, journalists, interest groups, and citizens. Thus a critically important broader impact of the RCN will be to foster improved public understanding of the roles and activities of the U.S. government.

http://poliinformatics.org/

Budget: Research Assistance. Travel to workshops. Conference attendance.

Work products: (2012) Workshop Report (2013) Conferences (2014) NSF-sponsored workshop  (2016) NSF-sponsored workshop

Dates: September 15 2012 – August 31, 2017

Application: May 2012 for Jan 2013 start. Awarded 4 months early

Steering Committee Members:
John Wilkerson    Political Science                               Professor, University of Washington    (Principal Investigator)
Anne Washington Legislative Information Systems  Asst. Professor, George Mason University (Co- Principal Investigator)
Christopher Adolph   Visualization and Statistics     Asst. Professor, University of Washington
Thomas R. Bruce      Legal Informatics                         Cornell Law School
Claire Cardie   Information Science                               Professor, Cornell University
Daniel Diermeier         Political Economy                     Professor, Northwestern University
John Gastil     Communication                                      Professor, Penn State University
Marie Ostendorf         Electrical Engineering              Professor, University of Washington
Noah Smith     Computer Science                                    Assoc. Professor, Carnegie Mellon University
Derek Willis    Data Journalism                                     The New York Times

Research Assistants: David C. Morar  Fall 2012 – Spring 2016