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Data Stewards are a growing role within scientific communities. ‘Data Steward’ is an umbrella term for numerous support roles that involve the creation, management and usage of research data (see also the Research Data Management chapter).

Black, white, grey and purple, cartoon-like sketch of two characters depicted as data stewards in superhero attire, with the left figure gesturing towards symbols of knowledge and alert, and the right figure pointing to tools of the trade such as security and connectivity, all encompassed by a theme of data management and protection.

Figure 1:A superhero-representation of the core responsibilities of a Data Steward. The Turing Way project illustration by Scriberia. Used under a CC-BY 4.0 licence. DOI: Community & Scriberia (2021).

What do Data Stewards do?

The core responsibilities of a Data Steward can vary, ranging from policy advisor/consultant, to hands-on operational tasks, to technical or ICT-related tasks. A Data Steward facilitates the quality, integrity and access to (meta)data in a manner that is consistent with the appropriate laws and institutional policies, ensuring professional treatment of data throughout all stages of the research project. See also: Verheul et al., 2019

Each role is varied but the main activities are typically focused around data, stewardship, and advising researchers:

The day-to-day tasks of a Data Steward could include:

What qualifications or skills do you need to be a Data Steward?

There is currently no formal track to take to become a Data Steward. Most Data Stewards have a masters or doctoral education, or a background in research and education. This background is needed to speak the same language as scientific staff, so that it becomes easier to understand their requirements and concerns. Depending on the particular focus of the position, you would need a more technical/ICT background, knowledge of discipline specific matters or experience with advising and policy construction. Soft skills are important in the advisory/policy roles, as you need to..

The “Towards FAIR data stewardship as profession” report (Scholtens et al., 2019) concluded that there are eight competency areas that of importance to Data Stewards:

  1. Policy/strategy: designing or raising awareness of research data management policies and regulations
  2. Compliance: advise on how to confer to research data management policies and regulations
  3. Facilitating FAIR/recommended research data management practices
  4. Services: propose, implement and monitor data management services and improve work processes
  5. Data infrastructure: identify requirements for infrastructure and tools
  6. Knowledge management: identify the level of research data management knowledge and skills
  7. Network and communication: set up networks to increase awareness and participate in (inter)national research data management networks
  8. Data sharing: archiving and publishing

Next to these specific areas coordination of work and development of soft skills may be important. See also: Jetten et al., 2021

Generally, Data Stewards acquire these skills through learning-on-the-job, which is facilitated by existing networks (see Organisations that support Data Stewards below). Through these networks experiences can be exchanged with peers, which is beneficial for personal and professional development. An examples of these collaborative efforts is the ‘23 Things: Support for Research Data’(Jetten et al., 2019) that provides a good overview of helpful resources for Data Stewards. Depending on the role of the Data Steward, learning discipline specific skills may be important through contributing to specific projects or attending conferences and meetings on relevant topics. As the research culture adapts to (inter)national changes, so too do the skills of the Data Steward that have to be continuously updated.

Challenges for Data Stewards

Benefits of having Data Stewards

Organisations that support Data Stewards

Summary

Data Stewards are an important part of scientific communities, supporting recommended data management practices and saving researchers time by supporting them in these efforts. They do not have a formal career path or qualifications, but typically have a scientific or research background themselves.

References
  1. Community, T. T. W., & Scriberia. (2021). Illustrations from The Turing Way: Shared under CC-BY 4.0 for reuse. Zenodo. 10.5281/ZENODO.5706310
  2. Verheul, I., Imming, Melanie, Ringersma, J., Mordant, A., Ploeg, J.-L. van der, & Pronk, M. (2019). Data Stewardship on the map: A study of tasks and roles in Dutch research institutes. Zenodo. 10.5281/zenodo.2669150
  3. Scholtens, S., Jetten, M., Böhmer, J., Staiger, C., Slouwerhof, I., van der Geest, M., & van Gelder, C. W. G. (2019). Final report: Towards FAIR data steward as profession for the lifesciences. Report of a ZonMw funded collaborative approach built on existing expertise. Zenodo. 10.5281/zenodo.3474789
  4. Jetten, M., Grootveld, M., Mordant, A., Jansen, M., Bloemers, M., Miedema, M., & van Gelder, C. W. G. (2021). Professionalising data stewardship in the Netherlands. Competences, training and education. Dutch roadmap towards national implementation of FAIR data stewardship. Zenodo. 10.5281/zenodo.4623713
  5. Jetten, M., Berg, B. van den, Kuzak, M., Witkowska, I., Karvovskaya, L., Teijeiro Barjas, C., Leenarts, E., Schoots, F., Cruz, M., Plomp, E., Verbakel, E., Martinez Lavanchy, P., Braaksma, B., Schoonhoven, R., & Verheul, I. (2019). 23 Things: Support for Research Data. Updated version for the Dutch Community by the LCRDM task group RDA/23 Things. Zenodo. 10.5281/zenodo.3465896