Practical considerations for a library’s research data management services: the case of the National Institutes of Health Library

Authors

  • Soojung Kim Jeonbuk National University Department of Library and Information Science
  • Sue Yeon Syn The Catholic University of America Department of Library and Information Science https://orcid.org/0000-0002-3632-5160

DOI:

https://doi.org/10.5195/jmla.2021.995

Keywords:

research data management, case study, library services

Abstract

Objective: This study investigates research data management (RDM) services using a crosstab framework with the National Institutes of Health (NIH) Library as a case study to provide practical considerations for libraries seeking to improve their RDM services.

Methods: We conducted semistructured interviews with four librarians who provide data services at the NIH Library regarding library user characteristics, RDM services provided, RDM infrastructure, and collaboration experiences. Through the analysis of interview transcripts, we identified and analyzed the NIH Library’s RDM services according to Online Computer Library Center (OCLC)'s three categories of RDM services and the six stages of the data lifecycle.

Results: The findings show that the two models’ crosstab framework can provide an overview of an institution’s current RDM services and identify service gaps. The NIH Library tends to take more responsibility in providing education and expertise services while relying more on information technology departments for curation services. The library provides significant support for data creation, analysis, and sharing stages to meet biomedical researchers’ needs, suggesting areas for potential expansion of RDM services in the less supported stages of data description, storage, and preservation. Based on these findings, we recommend three key considerations for libraries: identify gaps in current services, identify services that can be supported via partnerships, and get regular feedback from users.

Conclusion: These findings provide a deeper understanding of RDM support on the basis of RDM service categories and the data lifecycle and promote discussion of issues to be considered for future improvements in RDM services.

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Published

2021-10-05

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Section

Original Investigation