Going qual in: Towards methodologically inclusive data work in academic libraries
Keywords:data literacy, qualitative research, academic libraries, qualitative data
Data literacy and research data services are a growing part of the work of academic libraries. Data in this context is often presumed to mean only numeric data or statistics, leaving open the question of what role qualitative research plays in services and programming for research data and data literacy. In this paper, we report on the results of interviews with academic librarians about their understanding of data literacy, qualitative research, and academic library infrastructure around qualitative research. From the interviews, we propose a model of data literacy that incorporates both interpretive and instrumental elements. We conclude with suggestions for incorporating qualitative data and analysis methods into academic library programming and services around data literacy and research data.
How to Cite
Copyright (c) 2022 Jessica Hagman, Hilary Bussell
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This license lets others remix, tweak, and build upon your work non-commercially, and although their new works must also acknowledge you and be non-commercial, they don’t have to license their derivative works on the same terms.
The Creative Commons-Attribution-Noncommercial License 4.0 International applies to all works published by IASSIST Quarterly. Authors will retain copyright of the work. Your contribution will be available at the IASSIST Quarterly website when announced on the IASSIST list server.