Limitations to success in academic data reference support

Jenny McBurney, Alicia Kubas

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


As secondary data become increasingly integrated into research and coursework across a widening variety of fields and disciplines, data reference is gaining traction as a major area of library research support. To examine the current landscape of data reference, we distributed a survey via regional and international library listservs asking librarians about their experiences and opinions related to their data reference work. For this paper, the full collected dataset was limited to only academic librarians who answer at least one data reference question per month in order to identify the unique needs of respondents doing reference work in academic institutions, with the ultimate goal of improving our own work as academic librarians at our institution. We used a grounded theory approach to analyze the qualitative survey response data, and supplemented this analysis with descriptive statistics and chi-square tests for the quantitative responses. Through this analysis, we identify a theoretical framework consisting of three themes relating to limitations to success where librarians must advocate for change in order to maintain and improve high-quality data reference work in the academic sphere: (1) technology and resource limitations, such as substandard database interfaces; (2) institutional limitations, such as insufficient staff time or resources dedicated to data reference; and (3) personal limitations, such as a lack of data skills. While librarians have varying levels of influence over each of these three areas, identifying and targeting these categories can help librarians and other data professionals focus resources and build cases for additional support from their library and campus administrators.

Original languageEnglish (US)
Pages (from-to)121-131
Number of pages11
JournalJournal of Librarianship and Information Science
Issue number1
StatePublished - Mar 2 2021

Bibliographical note

Funding Information:
The authors would like to thank Andrew Kubas for assistance with quantitative data analysis and Danya Leebaw and Cody Hennesy for their feedback on the manuscript. The author(s) received no financial support for the research, authorship, and/or publication of this article.

Publisher Copyright:
© The Author(s) 2021.


  • Academic libraries
  • data librarianship
  • data reference services
  • grounded theory
  • library research support


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