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Cited by 106Research Data Management PracticesLibrary Science and InformationLibrary Science and Information Literacy

Defining data librarianship: a survey of competencies, skills, and training

Open access
Federer, Lisa·2018·Journal of the Medical Library Association
DOI 10.5195/jmla.2018.306PMC PMC6013124
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Abstract

OBJECTIVES: Many librarians are taking on new roles in research data services. However, the emerging field of data librarianship, including specific roles and competencies, has not been clearly established. This study aims to better define data librarianship by exploring the skills and knowledge that data librarians utilize and the training that they need to succeed. METHODS: Librarians who do data-related work were surveyed about their work and educational backgrounds and asked to rate the relevance of a set of data-related skills and knowledge to their work. RESULTS: Respondents considered a broad range of skills and knowledge important to their work, especially "soft skills" and personal characteristics, like communication skills and the ability to develop relationships with researchers. Traditional library skills like cataloging and collection development were considered less important. A cluster analysis of the responses revealed two types of data librarians: data generalists, who tend to provide data services across a variety of fields, and subject specialists, who tend to provide more specialized services to a distinct discipline. DISCUSSION: The findings of this study suggest that data librarians provide a broad range of services to their users and, therefore, need a variety of skills and expertise. Libraries hiring a data librarian may wish to consider whether their communities will be best served by a data generalist or a subject specialist and write their job postings accordingly. These findings also have implications for library schools, which could consider adjusting their curricula to better prepare their students for data librarian roles.

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  • Data-related tasks are often embedded within traditional roles and distributed across multiple units rather than formalised as distinct positions.

    “often embedded within traditional roles and distributed across multiple units rather than formalised as distinct positions”

    From Librarians’ roles and responsibilities in managing data within academic libraries: A role-based data governance model (2026) · cites this paper as Federer, 2018

    The Introduction (page unavailable) says some libraries assign data services to liaison librarians as part of broader duties, while others hire dedicated data-services staff. The Results (Participant characteristics; page unavailable) show that most respondents also did non-data work. These passages support embedding data tasks in broader roles, but do not establish that the tasks are distributed across multiple organizational units. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Most data work in libraries remains embedded within traditional roles.

    “Despite the emergence of specialised titles, most data work in libraries remains embedded within traditional roles.”

    From Librarians’ roles and responsibilities in managing data within academic libraries: A role-based data governance model (2026) · cites this paper as Federer, 2018

    The Introduction says some libraries assign data services to liaison librarians as part of broader duties, while others hire dedicated specialists. In Results > Participant characteristics (page unavailable), only 5% of surveyed data professionals reported spending all their time on data work. These passages support overlap with existing duties, but do not establish that most data work across libraries remains embedded in traditional roles; the survey focused on biomedical and science services. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • The embedded and distributed nature of data work in academic libraries is reflected in these findings.

    “This reflects the embedded and distributed nature of data work in academic libraries (Federer, 2018;Luo & Tang, 2024) and confirms that the proposed governance model is not a call for new positions, but a framework for recognising responsibilities already performed within existing roles.”

    From Librarians’ roles and responsibilities in managing data within academic libraries: A role-based data governance model (2026) · cites this paper as Federer, 2018

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Cited by

Sorted by citations

Authors
Federer, L.
Affiliations
National Institutes of Health (US)
Corresponding author
Federer, Lisa
ORCID
Federer, Lisa
Venue
Journal of the Medical Library Association
Publisher
University Library System, University of Pittsburgh
Published
2018-07-02
Volume
106
Issue
3
Pages
294-303
ISSN
  • 1536-5050 (ISSN-L)
  • 1558-9439
DOI
10.5195/jmla.2018.306
PMC
PMC6013124
OpenAlex
W2811308712
Cited by
106
References
0
Citations by year
2026: 9 · 2025: 6 · 2024: 12 · 2023: 10 · 2022: 14 · 2021: 18 · 2020: 19 · 2019: 12 · 2018: 2 · 2017: 3 · 2012: 1
FWCI
20.58
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of the Medical Library Association JMLA (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
  • Physical Sciences › Computer Science › Information Systems › Library Science and Information
  • Social Sciences › Library and Information Sciences › Library Science and Information Literacy
Keywords
data librarianship, research data services, librarian competencies, librarian training, subject specialists, soft skills, communication skills, library school curriculum, library cataloging, collection development
MeSH terms
Data Collection, Humans, Libraries, Medical, Professional Competence, Surveys and Questionnaires, Specialization, Librarians

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