Data Curation through Catalogs: A Repository-Independent Model for Data Discovery
- Helenmary Sheridan (University of Pittsburgh, Health Sciences Library System)
- Anthony J. Dellureficio (Memorial Sloan Kettering Cancer Center)
- Melissa A. Ratajeski (University of Pittsburgh, Health Sciences Library System)
- Sara Mannheimer (Montana State University)
- Terrie R. Wheeler (Weill Cornell Medicine)
Institutional data repositories are the acknowledged gold standard for data curation platforms in academic libraries. But not every institution can sustain a repository, and not every dataset can be archived due to legal, ethical, or authorial constraints. Data catalogs—metadata-only indices of research data that provide detailed access instructions and conditions for use—are one potential solution, and may be especially suitable for "challenging" datasets. This article presents the strengths of data catalogs for increasing the discoverability and accessibility of research data. The authors argue that data catalogs are a viable alternative or complement to data repositories, and provide examples from their institutions' experiences to show how their data catalogs address specific curatorial requirements. The article also reports on the development of a community of practice for data catalogs and data discovery initiatives.
Keywords: data catalog, data governance, data discovery, metadata record, data curation, DCN
How to Cite:
Sheridan, H. & Dellureficio, A. J. & Ratajeski, M. A. & Mannheimer, S. & Wheeler, T. R., (2021) “Data Curation through Catalogs: A Repository-Independent Model for Data Discovery”, Journal of eScience Librarianship 10(3): 4. doi: https://doi.org/10.7191/jeslib.2021.1203
Rights: © 2021 Sheridan et al. This is an open access article licensed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike License.