From Preserving the Past to Preserving the Future: The Data-PASS Project and the Challenges of Preserving Digital Social Science Data
Myron Gutmann, Mark Abrahamson, Margaret Adams, Micah Altman, Caroline Arms, Kenneth Bollen, Michael Carlson, Jonathan Crabtree, Darrell Donakowski, Gary King, Jaret Lyle, Marc Maynard, Amy Pienta, Richard Rockwell, Lois Rocms-Ferrara, Copeland Young. 2009.
"From Preserving the Past to Preserving the Future: The Data-PASS Project and the Challenges of Preserving Digital Social Science Data".
Library Trends, 57, Pp. 315–337.

Abstract
Social science data are an unusual part of the past, present, and future of digital preservation. They are both an unqualified success, due to long-lived and sustainable archival organizations, and in need of further development because not all digital content is being preserved. This article is about the Data Preservation Alliance for Social Sciences (Data-PASS), a project supported by the National Digital Information Infrastructure and Preservation Program (NDIIPP), which is a partnership of five major U.S. social science data archives. Broadly speaking, Data-PASS has the goal of ensuring that at-risk social science data are identified, acquired, and preserved, and that we have a future-oriented organization that could collaborate on those preservation tasks for the future. Throughout the life of the Data-PASS project we have worked to identify digital materials that have never been systematically archived, and to appraise and acquire them. As the project has progressed, however, it has increasingly turned its attention from identifying and acquiring legacy and at-risk social science data to identifying on going and future research projects that will produce data. This article is about the project’s history, with an emphasis on the issues that underlay the transition from looking backward to looking forward.
See Also
- [Presentation] Empowering Social Science to Understand and Ameliorate Major Challenges of Human Society (Federal Interagency Conference on Social Science and Big Data) (2020)
- [Paper] Preserving Quantitative Research-Elicited Data for Longitudinal Analysis. New Developments in Archiving Survey Data in the U.S. (2009)
- [Presentation] Empowering Social Science Research With Industry Partnerships (Dean's Symposium on Social Science Innovations, Harvard) (2021)
- [Paper] A Digital Library for the Dissemination and Replication of Quantitative Social Science Research (2001)
- [Presentation] Big Data Reveals Made Up Data: How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument (2017)
- [Presentation] The Next Big [Social Science] Thing. Some Suggestions for Science Magazine (2015)
- [Presentation] Dataverse: Sharing Research Data; Building Social Science (2014)
- [Paper] Restructuring the Social Sciences: Reflections from Harvard's Institute for Quantitative Social Science (2014)