Data Curation and Preservation

Preserving research data for continued access and use

Research data curation and preservation has emerged as a major initiative in many countries through efforts within research communities as well funding and government agencies. The D2I team contributes to this global effort by studying the processes, organizations, and technologies needed to maintain research data over time. Our collaborators include academic libraries, data sharing platforms and projects, such as DataONE, global organizations, such the Research Data Alliance (RDA) and academic units within universities, such as the Ostrom Workshop.

The D2I team was the main contributor to the SEAD project -  a platform that enables management of data across a broad range of physical and social science disciplines and with the goal of reducing the effort required to curate and preserve data for long-term use. The project ran between 2011 and 2017 and is now offered as a resource through the National Data Service Consortium (NDS).

For more information and additional projects, please see the Storage and repositories sections on Open source software.

Selected Publications

  • Beth Plale and Inna Kouper. 2017. The centrality of data: Data lifecycle and data pipelines. In Data analytics for intelligent transportation systems, Mashrur A. Chowdhury, Amy Apon and Kakan Dey (eds.). Elsevier Inc., Cambridge, MA, 91–111. Retrieved June 20, 2017 from (pdf)
  • Dharma Akmon, Margaret Hedstrom, James D. Myers, Anna Ovchinnikova, and Inna Kouper. 2017. Building tools to support active curation: Lessons learned from SEAD. International Journal of Digital Curation 12, 2.
  • Inna Kouper, Kathleen Fear, Mayu Ishida, Christine Kollen, and Sarah C. Williams. 2017. Research Data Services Maturity in Academic Libraries. In Curating Research Data, Volume 1: Practical Strategies for Your Digital Repository, Lisa R Johnston (ed.). ACRL, Washington, DC. Retrieved February 21, 2017 from
  • Beth Plale, Inna Kouper, Alison Goodwell, and Isuru Suriarachchi. 2016. Trust Threads: Minimal Provenance for Data Publishing and Reuse. In Big Data is Not a Monolith: Policies, Practices and Problems, Cassidy R. Sugimoto, Hamid Ekbia and Michael Mattioli (eds.). MIT Press. (pdf)