Reflecting on Key Performance Indicators for Research Data Management Initiatives

For NFDI4ING, the first funding period of the first consortia is coming to an end in September 2025, with a possibility for a second funding period. To collect the results generated, the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) has provided NFDI4ING consortia with a supplementary data sheet, which breaks down the accomplishments of the consortia into key performance indicators (KPIs) [1]. However, some KPIs are easier tracked while some are harder to maintain. One example are KPIs for Services, as these have very different scopes and goals, which are not easily commonly measured. Additionally, some KPIs can be collected differently depending on the interpretation of the supplementary data sheet. Unless there is a common understanding by the ones recording and evaluating KPIs, measuring activities effectively and as intended is hindered significantly. This is relevant both within NFDI4ING, as well as other NFDI consortia. Even when a common understanding of the supplementary data sheet exists within a consortium, for instance in NFDI4ING, the collection of KPIs can be challenging. Additionally, the comparability between NFDI consortia or other research initiatives is lacking. This even applies despite the fact that KPIs of DFG supplementary data sheet are primarily meant for comparison of the development of each of the consortia on themselves. Furthermore, this issue is not limited to NFDI4ING alone but also affects other research initiatives, for example DFG founded "Fachinformationsdienste f ¨ur die Wissenschaft" (FID, Specialised Information Services). CoRDI offers a unique opportunity to discuss such issues. Hence, NFDI4ING and FID move propose a common workshop to discuss the recording of KPIs in the context of research supporting initiatives. Goal of this workshop is the gathering of problems faced by participants when collecting KPIs and ideas on how to solve these problems. The workshop will follow the TRIZ Liberating Structures approach by Kubelke and Schmitt [2] and is planned for approximately 90 minutes. Firstly, participants collaboratively create a list of hurdles and challenges that would guarantee failure in reaching certain KPIs. Through this process, the participants engage in "creative destruction", identifying counterproductive practices that are considered unspoken. This approach follows three steps: 1. List the worst hurdles and challenges: Together, participants brainstorm activities or hurdles to ensure the worst possible outcome, e.g. not reaching a single entry in a specific KPI. 2. Identify real-life parallels: Participants reflect honestly on current behaviours that could cause those worst-case actions. 3. Decide what to change: Participants determine which of these behaviours should be stopped and how to take the first steps toward doing so. Kickstarting a reflective and constructive dialogue, the TRIZ Liberating Structures approach enables the identification of hidden dysfunctions and allows for a new and beneficial perspective on the collection of KPIs. The results will give a better understanding for all participants on how to address challenges when recording KPIs. Additionally, common problems and their solutions can give the institutions asking for KPIs an impression on how KPIs can be improved in the future.