In today's data-driven landscape, the role of data stewards has become indispensable as organizations grapple with escalating complexity and volumes of data. However, the term Data Stewardship still carries a degree of abstraction and lacks clarity. The need to elucidate its meaning, particularly within the context of NFDI-MatWerk, has drawn significant attention. What specific advantages does the role of data stewardship offer to researchers in the field of material sciences?

These abstract outlines the theoretical framework of data stewardship for NFDI-MatWerk, tracing its evolution from the establishment of the NFDI-MatWerk consortium. It explores the development of responsibilities, MatWerk's activities, consulting researchers, and the dynamic interaction between data stewardship within the consortium and its counterparts at universities.

The data stewards are professionalized within a project and mostly for a project [1]. The expertise, competence, and acquired knowledge of data stewards have given rise to a bottom-up approach in outlining how they can offer effective support in the MSE community. This perspective does not negate the other intermediary roles of data stewards but rather highlights how this sequencing of tasks can function particularly well in this context (Figure below).

Within the MatWerk consortium, the TA-MDI (a consortium subgroup) developed a service architecture [3]. Leveraging this architecture, data stewards assist MSE researchers in maximizing the use of a set of services vetted and endorsed by MatWerk specialists for the MSE community.

Data stewards tackle and resolve challenges outlined in Infrastructure Use Cases (IUCs). A tangible demonstration is the NFDI-MatWerk Infrastructure Use Case 05 [4] focusing on "Digital infrastructure and workflows for labs''. It concentrates on special skills in research data management required in MSE experimental labs, e.g. metadata for data acquisition, creating and documenting data processing workflows, etc.

Beyond fundamental responsibilities, data stewardship provides the MSE community with a tailored set of skills and procedures designed to effectively meet their requirements. This unwavering support begins early in the MSE requirements identification process, collaborating with scientists to shape Infrastructure Use Cases (IUCs). This support extends throughout development and culminates in the delivery of services. Further detailed insights in this regard will be presented in the subsequent sections of the presentation.

Acknowledgments

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under the National Research Data Infrastructure – NFDI 38/1 – project number 460247524.

References

[1] Salome Scholtens, „Final report: Towards FAIR data steward as profession for the lifesciences. Zenodo, Oct. 03, 2019. doi: 10.5281/zenodo.3474789.

[2] A. Daei Rezaei Moghaddam, „Effective Data Stewardship in NFDI-MatWerk“. Zenodo, Jan. 25, 2024. doi: 10.5281/zenodo.10566837.

[3] Y. Shakeel ; S. Hunke DOI:10.5445/IR/1000161225

[4] https://nfdi-matwerk.de/infrastructure-use-cases/iuc05-digital-infrastructure-and-workflows-for-labs