To attain a representative view of the state-of-play of Research Data Management at TU Graz, potential candidates for interviews were selected based on two factors: Their affiliation (faculty/department) and their position. The target was to interview a minimum of two people per faculty (regardless of department). This target has not been met, in part due to recruiting issues, although it should be noted that we ended up interviewing more candidates than we had planned. Additionally, departmental structures do not necessarily reflect differences in data management; therefore, the interviews we have been able to conduct provide a good overview of data management practices at TU Graz regardless of institutional affiliations. In total, 13 formal interviews were conducted with a total of 18 respondents holding various positions at their departments/faculties. Three formal meetings held at the Faculties for Architecture, Electrical Engineering, and Mechanical Engineering were included in the analysis (protocols were crafted during the meetings). Interview partners were identified by manually scanning TUGonline by faculty, initially identifying one-two researchers per faculty, all researchers with a teaching qualification according to their TUGonline profiles (Professors and Associate Professors), though it must be stressed that this strategy was not always successful. Additionally, deans of faculty were approached to name potential interviewees, but this strategy has not proved very effective. Researchers were contacted via email requesting an interview on data practices and, foregoing a positive response, to name alternative candidates. Those who declined did so for one of two reasons: (self-ascribed) lack of competence in the subject of data management, or general refusal to give interviews. Fortunately, those in the first group shared names of potential interviewees they considered to be a better fit.
For the interviews, we used a formalized list of interview questions along with possible follow-up questions to fall back on should the conversation come to a halt at any point. The questions were formulated in an open fashion to be able to record as much potential variation in the answers between cases as possible. All interviews have been professionally transcribed and coded using the software package Rqda. Coding was done by one researcher, with supervision and feedback from other researchers. The material was analysed paying special attention to data practices (types of data used by disciplines, methods of data collection, storage, and analysis, data sharing routines - or lack thereof). The interview questionnaire was designed to allow reconstruction of data handling practices in their wider institutional, disciplinary and practical context. The semi-standardized interview questionnaire contained broad questions about data in the context of research, (typical) research aims, data management practices, roles, and responsibilities, data storage and data sharing, and research culture more broadly (e.g. publication routines, reputation and credit, etc.). In keeping with the findings from initial gatekeeper contact, the interview questions refrained from using terms such as “research data management”, “data management”, and “policy”, and instead focused on understanding what researchers do with their data, a strategy which has proved worthwhile.