Panel Session at Research Data Access and Preservation (RDAP) Summit, March 29, 2023, Session 5-B, 3:00pm-4:00pm | RECORDING

Moderator: Lynda Kellam, University of Pennsylvania

Panelists: Mandy Swygart-Hobaugh, Georgia State University | Jessica Hagman,  University of Illinois, Urbana-Champaign | Hillary Bussell, Ohio State University | Dessi Kirilova, Qualitative Data Repository

Academic data services covers a wide range of activities from GIS to computational techniques to data management. Qualitative data support is often lost in the shuffle despite researchers needing assistance with the methods, software support, and knowledge on data sharing and archiving. The qualitative data librarian community has been small but vocal in bringing attention to these issues. This panel will discuss both the past and present of qualitative data support in libraries. Mandy Swygart-Hobaugh will talk about the past efforts to support qualitative data, and Jessica Hagman will talk about her research on the current state of qualitative data support. Moreover, Hilary Bussell has examined ways to provide sustainable models for qualitative data support. Finally, we will be joined by Dessi Kirilova with the Qualitative Data Repository who will talk about QDR’s experiences working with librarians and the challenges researchers face in sharing their qualitative data. Our panel will first focus on three major topics: defining qualitative data support, the possibilities and challenges for sustaining qualitative data support in the libraries, and finally the ethical issues in sharing qualitative data. Within these topics we will address the following questions among others: 1) How do you describe services for qualitative researchers in a way that is inclusive of the wide variety of data types, methods, and research paradigms that might be used? 2) Where does qualitative data work happen in your library? What are strengths/weaknesses of this approach? and 3) How does data management support for qualitative work address the unique ethical concerns, particularly when the data relates to systematically marginalized communities?