German funders' data sharing policies: a qualitative interview study [interview excerpts] - Anger, Michael; Wendelborn, Christian; Schickhardt, Christoph (Universität, 2023)
Background Data sharing is commonly seen as beneficial for science, but is not yet common practice. Research funding agencies are known to play a key role in promoting data sharing, but German funders’ data sharing policies appear to lag behind in international comparison. This study aims to answer the question of how German data sharing experts inside and outside funding agencies perceive and evaluate German funders’ data sharing policies and overall efforts to promote data sharing. Methods This study is based on sixteen guideline-structured interviews with representatives of German funding agencies and German research data experts from other organisations, who shared their perceptions of German’ funders efforts to promote data sharing. By applying the method of qualitative content analysis to our interview data, we categorise and describe noteworthy aspects of the German data sharing policy landscape and illustrate our findings with interview passages. Research data This dataset contains summaries from interviews with data sharing and funding policy experts from German funding agencies and what we call "stakeholder organisations" (e.g., universities, research data infrastructure providers, etc.). We asked the interviewees about their perspectives on German funders' data sharing policies, for example regarding the actual status quo, their expectations about the potential role that funders can play in promoting data sharing, as well as general developments in this area. Supplement_1_Interview_guideline_funders.pdf and Supplement_2_Interview_guideline_stakeholders.pdf provide supplemental information in the form of the (german) interview guidelines used in this study. Supplement_3_Transcription_and_coding_guideline.pdf lays out the rules we followed in our transcription and coding process. Supplement_4_Category_system.pdf describes the underlying category system of the qualitative content analysis we conducted. (2023-06-11)
Gesehen am 15.08.2023
Keywords: Forschungsdaten; Datenbank