The German Reproducibility Network: Strengthening Research Data Management through Cross-Disciplinary Collaboration and Open Science Education

The German Reproducibility Network (GRN) is a cross-disciplinary consortium that aims to increase trustworthiness and transparency of scientific research by investigating and encouraging the factors that contribute to reproducible and robust research. Since the inception in 2020 it has grown to over 45 institutional and grassroots members [1]. The GRN serves as a platform for collaboration among early career and senior researchers, academic institutions, and scholarly societies, promoting a cultural shift towards open and reproducible research practices. The GRN emphasizes the crucial role of Research Data Management (RDM) as part of broader efforts towards reproducibility. We organize educational programs like Summer Schools aiming at embedding Open Science and FAIR (Findable, Accessible, Interoperable, and Reusable) principles into the daily workflows of researchers. Notably, at the RDA Germany Conference 2023, we organized a session titled Enabling reproducibility in data science [2]. At the deRSE24 we gave a workshop addressing FAIR and reproducible coding practices [3]. These contributions reflect our ongoing commitment to fostering cultural change and enhancing RDM capabilities across disciplinary boundaries. Furthermore, the GRN contributes to strategic policy discussions and structural advocacy within the German research landscape, emphasizing sustainable integration of open data practices into institutional policies and research evaluation frameworks. Therefore we issued an Open Data Statement in cooperation with our members [4]. Our advocacy around the WissZeitVG reform highlighted the necessity of good working conditions in academia to facilitate RDM and reproducibility [5]. At CoRDI 2025, under the track "RDM in Context," the GRN seeks to share experiences and outcomes from our interdisciplinary approach to fostering a culture of reproducible research. We will highlight examples from previous initiatives, discuss encountered challenges, and explore opportunities for further collaboration in standardizing and supporting open and reproducible research practices.