Qualitative Data Sharing: Data Repositories and Academic Libraries as Key Partners in Addressing Challenges. (May 2019)

• Record Type: Journal Article
• Authors: Mannheimer, Sara; Pienta, Amy; Kirilova, Dessislava; Elman, Colin; Wutich, Amber
• Other Names: Glenna Leland guest-editor.; Hesse Arielle guest-editor.
• Is Part Of: American behavioral scientist. Volume 63:Number 5(2019)
• Page Start: 643
• Page End: 664
• Publication Date: 2019-05
• Subjects: data sharing -- qualitative data -- library data services -- data repositories; Social sciences -- Periodicals; Political science -- Periodicals; United States -- Social conditions -- Periodicals; United States -- Politics and government -- Periodicals; 300
• DOI: 10.1177/0002764218784991
• Languages: English
• ISSNs: 0002-7642

Abstract

Data sharing is increasingly perceived to be beneficial to knowledge production, and is therefore increasingly required by federal funding agencies, private funders, and journals. As qualitative researchers are faced with new expectations to share their data, data repositories and academic libraries are working to address the specific challenges of qualitative research data. This article describes how data repositories and academic libraries can partner with researchers to support three challenges associated with qualitative data sharing: (1) obtaining informed consent from participants for data sharing and scholarly reuse, (2) ensuring that qualitative data are legally and ethically shared, and (3) sharing data that cannot be deidentified. This article also describes three continuing challenges of qualitative data sharing that data repositories and academic libraries cannot specifically address—research using qualitative big data, copyright concerns, and risk of decontextualization. While data repositories and academic libraries cannot provide easy solutions to these three continuing challenges, they can partner with researchers and connect them with other relevant specialists to examine these challenges. Ultimately, this article suggests that data repositories and academic libraries can help researchers address some of the challenges associated with ethical and lawful qualitative data sharing.