Living the NFDI on Campus
Data stewardship plays a central role in translating the NFDI endeavor of making research data FAIR into everyday scientific practice. Within DataPLANT, stewardship activities initially emerged from a data-centric perspective focused on supporting researchers close to the laboratory bench: guiding and improving metadata annotation of experimental workflows and helping researchers transform daily routines into FAIR research data.
Over time, this role evolved beyond technical data management support. Data stewards engage as mediators between research practice and infrastructure development, translators between community needs and technical implementation, trainers for researchers with diverse levels of data literacy and AI-readiness, and advocates for FAIR and digital research practices. Through workshops, hands-on support, and continuous interaction with researchers, data stewardship activities identified practical gaps, such as missing annotation concepts for various data types, missing ontology terms, missing functionalities, usability barriers, and limitations in existing workflows and tooling. This feedback loop directly informs the development and adoption of DataPLANT concepts, tools, and services.
At the same time, the stewardship model continuously evolved alongside the broader development of DataPLANT, the NFDI landscape, and emerging national and international FAIR data initiatives. This recurring alignment between local community requirements and the rapidly changing research data landscape enabled stewardship activities to act not only as operational support, but also as a bidirectional feedback and integration layer between research, infrastructure development, and institutional decision-making. Over time, the role of data stewards gradually expanded from supporting individual researchers and projects towards contributing to the alignment of institutional RDM practices with consortium-wide and national FAIR data strategies.
Using DataPLANT as an example, we reflect on how NFDI services and stewardship practices were progressively integrated into local research workflows, institutional structures, and policy development. The close alignment between community engagement, open-source infrastructure development, and institutional adoption enabled a transition from experiment-centered data support towards publication workflows and bringing FAIR Digital Object (FDO) publications to life. At the same time, stewardshipactivities revealed recurring tensions between standardization and usability, stability and innovation, and local research versus interoperable infrastructure requirements. We highlight data stewardship as a human interface and coordination layer within the NFDI landscape — connecting infrastructure, policy, and research culture — and discuss how community-oriented stewardship practices can facilitate the sustainable adoption of FAIR research data practices within and across scientific communities.
