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Curriculum Data Deep Dive: Identifying Data Literacies in the Disciplines

  • Christina M Klenke (University of Nevada, Reno)
  • Teresa Auch Schultz (University of Nevada, Reno)
  • Rayla E. Tokarz (University of Nevada, Reno)
  • Elena S Azadbakht (University of Nevada, Reno)


Objective: Evaluate and examine Data Literacy (DL) in the supported disciplines of four liaison librarians at a large research university.

Methods: Using a framework developed by Prado and Marzal (2013), the study analyzed 378 syllabi from a two-year period across six departments—Criminal Justice, Geography, Geology, Journalism, Political Science, and Sociology—to see which classes included DLs.

Results: The study was able to determine which classes hit on specific DLs and where those classes might need more support in other DLs. The most common DLs being taught in courses are Reading, Interpreting, and Evaluating Data, and Using Data. The least commonly taught are Understanding Data and Managing Data skills.

Conclusions: While all disciplines touched on data in some way, there is clear room for librarians to support DLs in the areas of Understanding Data and Managing Data.

Keywords: Data Literacies, Data Competencies, Research Data Management, Data Services, Case Study, Academic Libraries, Open Data, Big Data, Data Skills, Reading Data, Interpreting and Evaluating Data, Using Data, Understanding Data, Managing Data

How to Cite:

Klenke, C. M., Auch Schultz, T., Tokarz, R. E. & Azadbakht, E. S., (2020) “Curriculum Data Deep Dive: Identifying Data Literacies in the Disciplines”, Journal of eScience Librarianship 9(1): 1. doi: https://doi.org/10.7191/jeslib.2020.1169

Rights: Copyright: © 2020 Klenke, Schultz, Tokarz, and Azadbakht. This is an open access article licensed under the terms of the Creative Commons Attribution License.

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Published on
03 Feb 2020