Open Access

Évariste Demandt, Zeynep Dirier, Manuel Feser, Fabian Fricke, Michael Goedicke, Gabin Oumbe, Christian Schmidt, Torsten Schrade, Thorsten Trippel, Lisa Amelung, Cord Wiljes, Elena Wössner

• Germany's National Research Data Infrastructure (NFDI, Nationale Forschungsdateninfrastruktur) comprises 26 consortia, each providing data management services for a specific domain or methodology. Consortia operate as cooperative projects funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). Additionally, the consortia are reflected as departments of the NFDI association. A central aim of NFDI is to cooperatively build a domainand method-spanning research data infrastructure embodied by the vision of OneNFDI, i.e., the desired convergence of multiple infrastructures for RDM across domains into a comprehensive, flexible network of interconnected services. This vision drives extensive cross-consortial collaboration facilitating data to become a common good for excellent research. Such collaborations include sections of the NFDI association addressing overarching topics ; the cross-consortia project Base4NFDI ; and task forces on governance, sustainability, evaluation and reporting, and the implementation of technical tools. NFDI as a whole needs to assess its impact as required by the Scientific Senate of NFDI and the Federal Ministry of Education and Research (BMBF), and each consortium must monitor progress and performance in serving their scientific communities. Therefore, a robust monitoring and reporting strategy is needed, built on overarching KPIs collected with a standardized, yet sufficiently flexible database facilitating both internal evaluation and external reporting. In 2023, the Task Force Evaluation and Reporting (TFER) compiled and devised criteria for quantitative and—importantly—qualitative performance indicators, introducing distinct definitions and parameters for reporting on each consortium's progress. These served as a reference for the DFG's design of a data sheet template with over 40 indicators, now compulsory in reports and follow-up proposals submitted to the DFG. Several indicators pose socio-technical challenges to ensuring accurate and meaningful assessment. To support consortia coordination offices and the NFDI office, a TFER subgroup evaluated the open-source database tool NocoDB. NocoDB integrates an intuitive spreadsheet-style frontend for user-friendly interaction with an SQL-based database backend, enabling API-based ingestion, querying, and retrieval of data. Its interoperability with third-party tools such as OpenProject, Mattermost Boards, Zotero, Zenodo, Apache Superset, N8N, and the Scorpion service indicator dashboard facilitates workflow integration, multi-tool pipelines, and alignment with the existing tool landscape across individual consortia. Here, we present the development of a standardized NocoDB table structure differentiating between curation tables for systematically recording indicators manually or API-based, and reference tables for streamlined retrieval of requested indicators in a standard format. This combined structure remains flexible in allowing individual consortia to extend it while maintaining a standardized exposure view enabling cross-consortial research on indicators. A consortium can obtain a partially pre-filled, templated NocoDB base to integrate into a self-hosted instance. Alternatively, a consortium can autonomously govern a base within a centrally hosted NFDI NocoDB instance available to all consortia in Q2/2025. With its focus on standardization, flexibility and ease of use, our approach may serve as a blueprint for collaborative KPI monitoring in large scale research data management projects. We concentrate on the process to achieve a common understanding of the information structures and the practical aspects of collecting related data in a valid way.