The BAM Data Store | Establishing an openBIS-Based Research Data Infrastructure in Materials Science and Engineering

With more than 1,000 scientific employees, the Federal Institute for Materials Research and Testing (BAM) conducts research, development, and technical services with high societal relevance [1]. By participating in several NFDI consortia and digitization projects that contribute to the standardization of Materials Science and Engineering (MSE) related (meta-)data, BAM is actively shaping the future of Research Data Management (RDM) [2], [3], [4]. As part of its institutional strategy to implement the FAIR data principles [5] and to sup-port researchers in the day-to-day management of research data. The eScience and IT sec-tions work together to establish a centralized RDM platform—the BAM Data Store. This platform is based on the open-source framework openBIS [6], [7], developed, and maintained by the Scientific IT Services of ETH Zurich in close collaboration with an active user community that includes several large institutions from MSE-related disciplines. The BAM Data Store project, active since 2021, aims to provide institution-wide services for infrastructure, training, and the definition of metadata standards. This contribution builds on insights shared at CoRDI-2023 [8] to provide an update on the institutional rollout of the sys-tem and highlight the strategies used to address challenges posed by BAM's scale and disci-plinary diversity. Key topics include the challenges of establishing a centralized RDM platform in a large, multidisciplinary organization, and the strategies used to ensure scalability, user acceptance, and sustainability. A particular focus is on the role of Data Store Stewards (DSSts)—researchers embedded in scientific groups who support the implementation and act as multipliers. Their engagement emphasizes the need to recognize RDM-related contributions as part of scientific output. From a technical and structural perspective, the Data Store leverages the flexible, entity-based data model of openBIS to represent heterogeneous MSE workflows. However, this agnosticism requires the development of harmonized, semantically enriched metadata schemas to ensure interoperability across the institution and beyond. Our ongoing efforts to define a generic yet extensible metadata model for MSE disciplines aim to connect institutional RDM practice with national and international standards. By presenting the BAM Data Store project, we contribute practical insights and implementation strategies for institutions facing similar challenges in infrastructure development, role definition, and metadata interoperability.