Data Curation through Catalogs: A Repository-Independent Model for Data Discovery

Author:

Sheridan Helenmary1ORCID,Dellureficio Anthony J.2ORCID,Ratajeski Melissa A.1ORCID,Mannheimer Sara3ORCID,Wheeler Terrie R.4

Affiliation:

1. University of Pittsburgh

2. Memorial Sloan Kettering Cancer Center

3. Montana State University

4. Weill Cornell Medicine

Abstract

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.

Publisher

University of Massachusetts Medical School

Subject

General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ontology-Driven Multi-Level Conceptual Modeling for Dataset and Distributions Descriptions;Frontiers in Artificial Intelligence and Applications;2023-12-21

2. The NYU Data Catalog: a modular, flexible infrastructure for data discovery;Journal of the American Medical Informatics Association;2023-07-06

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