Between administration and research: Understanding data management practices in an institutional context
基于一所奥地利STEM大学的调查和访谈，揭示了不同院系在数据管理实践上的差异，指出数据管理常被视为行政任务而忽视研究质量，并区分了通用与学科特定问题。
Abstract Research Data Management (RDM) promises to make research outputs more transparent, findable, and reproducible. Strategies to streamline data management across disciplines are of key importance. This paper presents results of an institutional survey ( N = 258) at a medium‐sized Austrian university with a STEM focus, supplemented with interviews ( N = 18), to give an overview of the state‐of‐play of RDM practices across faculties and disciplinary contexts. RDM services are on the rise but remain somewhat behind leading countries like the Netherlands and UK, showing only the beginnings of a culture attuned to RDM. There is considerable variation between faculties and institutes with respect to data amounts, complexity of data sets, data collection and analysis, and data archiving. Data sharing practices within fields tend to be inconsistent. RDM is predominantly regarded as an administrative task, to the detriment of considerations of good research practice. Problems with RDM fall in two categories: Generic problems transcend specific research interests, infrastructures, and departments while discipline‐specific problems need a more targeted approach. The paper extends the state‐of‐the‐art on RDM practices by combining in‐depth qualitative material with quantified, detailed data about RDM practices and needs. The findings should be of interest to any comparable research institution with a similar agenda.