Excel for data visualization in academic health sciences libraries: a qualitative case study

Authors

  • Fred Willie Zametkin LaPolla Research and Data Librarian, NYU Health Sciences, and Liaison, Departments of General Internal Medicine and Radiology, New York University Langone Health (NYU Langone), New York, NY https://orcid.org/0000-0002-3185-9753

DOI:

https://doi.org/10.5195/jmla.2020.749

Keywords:

Data Visualization, Microsoft Office, Library Outreach, Library Instruction, Data Services, Data, Data Analysis, Qualitative Studies, Qualitative Case Studies

Abstract

Background: Data visualization is a growing topic of discussion and area of educational programming in health sciences libraries. This paper synthesizes information on eight institutions’ experiences in offering Excel-focused data visualization workshops with the goal of providing an overview of the current state of educational offerings in this area.

Methods: Semi-structured interviews were conducted by phone and email with librarians at institutions that offer Excel-focused workshops, which were identified by reviewing the websites of Association of Academic Health Sciences Libraries members and the 2019 Medical Library Association annual meeting program.

Results: Librarians from six institutions were interviewed, online class materials from one institution were reviewed, and information from the author’s institution was included, resulting in a total of eight institutions. Educational offerings in Excel-focused data visualization ranged from one workshop to five workshops in a series, which typically first presented information for beginners and then progressed to more advanced data visualization skills. Regarding motivations for offering these workshops, librarians stated that they were committed to providing instruction in software programs that were already familiar to users. Workshop evaluations, when available, were generally positive.

Discussion: Because of its widespread availability and usage, Excel offers a compelling opportunity for providing hands-on data visualization instruction in health sciences libraries.

References

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Published

2020-01-02

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Section

Original Investigation