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Minimum Viable Skills for Data Steward

The Minimum Viable Skillset (MVS) sets out to describe a shared framework for the recognition of competencies required for Open Science practitioners. Data Stewards are one of the key Open Science practitioners.

Minimum Viable Skillsets for Data Stewards are described in two profiles:

These represent two ends of a spectrum, with Coordinator describing a role providing support across research domains and units relevant to an organisation, and Embedded describing a role close to a research team and to its domain-specific practices. We acknowledge that these roles can overlap, influenced by the availability of resources, and by disciplinary and organisational cultures. We also acknowledge that a variety of other job titles may perform the data stewardship roles described here, e.g. Data Curator, Data Librarian, Data Manager, as well as Data Steward.

The two Data Steward MVS describe expertise needed to maximise the potential value of digital research objects for the scientific community and the public, while respecting the rights and legitimate interests of all other stakeholders concerned. These include data subjects, the researchers and organisations that produce data and other digital research objects, any vulnerable groups or communities affected, research funders, scientific journals, repositories, and other Research Data Infrastructures.

Data Stewardship expertise is typically distributed across a team, drawing on in-house capabilities and any external services provided to the Research Performing Organisation, e.g. by a Competence Centre. The appropriate distribution of expertise will naturally depend on costs and needs, and will be influenced by disciplinary factors as well as the availability of skills to meet local needs.

Data Stewards perform key roles in the EOSC. As practitioners and champions of Open Science, and as trainers and enablers of others in their organisation (researchers especially), they are likely to be both consumers and providers of services or resources.

References

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  1. Christian Wendelborn, Michael Anger, and Christoph Schickhardt. What is data stewardship? towards a comprehensive understanding. Journal of Biomedical Informatics, 140:104337, 2023. URL: https://www.sciencedirect.com/science/article/pii/S1532046423000588, doi:https://doi.org/10.1016/j.jbi.2023.104337. ↩

  2. EOSC Future. Learning paths. 2023. URL: https://wiki.eoscfuture.eu/display/PUBLIC/Learning+Paths. ↩