Managing complexity in research data management for heterogeneous biotechnological data: a perspective on interacting as data steward.

Biotechnology is an interconnected and globally significant field with expanding impact on industries, bioeconomy and healthcare. The associated rapid increase in data generation requires effective research data management (RDM) that ensures compliance with the FAIR principles (findable, accessible, interoperable and reusable) while addressing challenges related to heterogeneous data formats, metadata complexity, data protection, and governance requirements. Furthermore, archiving and storage of heterogeneous, often proprietary data formats, and subject-specific ontologies in cross-domains can pose challenges for RDM. In a use case involving 50 international, cross-discipline biotechnology researchers, an institutional repository was used for RDM and to manage heterogeneous data formats such as experimental, computer-aided modeling and process engineering data in accordance with the FAIR principles. The RDM built on the repository's existing centralized infrastructure, but this did not entirely meet user expectations for their practical research applications. While centralized top-down infrastructures of repositories provided the technical foundation for FAIR data handling, our observation showed that generic repository frameworks and standardized workflows required continuous, discipline-specific, and human mediated support integrated into everyday research workflows. As intermediaries between institutional requirements and research practice, data stewards can provide valuable insights into the challenges of implementing sustainable RDM helping to optimize repository support structures and align them with researchers' evolving needs in complex real-world biotechnology research environments.