The Development of a Research Data Policy at Wageningen University & Research: Best Practices as a Framework

Abstract

The current case study describes the development of a Research Data Management policy at Wageningen University & Research, the Netherlands. To develop this policy, an analysis was carried out of existing frameworks and principles on data management (such as the FAIR principles), as well as of the data management practices in the organisation. These practices were defined through interviews with research groups. Using criteria drawn from the existing frameworks and principles, certain research groups were identified as 'best-practices': cases where data management was meeting the most important data management criteria. These best-practices were then used to inform the RDM policy. This approach shows how engagement with researchers can not only provide insight into their data management practices and needs, but directly inform new policy guidelines.

Research data management systems and the organization of universities and research institutes: A systematic literature review

“…Cox and Verbaan (2018) confirmed this perspective and explained that pilot services could be useful “to prove the nature of need” (p. 96). Furthermore, Schmidt and Dierkes (2015) as well as van Zeeland and Ringersma (2017) emphasized the importance to incorporate users for the development of policies and guidelines because these documents must correspond to various needs of the research disciplines. In addition, the studies revealed that besides the institutional policy also the funder as well as the journal data policy influence the behavior of scientists (Briney et al, 2017; Higman and Pinfield, 2015).…”

“…This incorporation can take place through questionnaires, interviews, or workshops (e.g. Clements, 2013; Cruz et al, 2019; Eifert et al, 2016; Knight, 2015; Liu and Ding, 2016; Mohammed and Ibrahim, 2019; Plomp et al, 2019; van Zeeland and Ringersma, 2017).…”

Cross-Functional Policy Development for a Data Repository

“…Literature on a library-based data repository policy exists in a few different categories. These include the following: explorations on the scope and content of a policy, including exploring the concepts and purpose of a repository policy (Riddle, 2015), emerging workflows in data management in a repository (Austin et al, 2017), and content analysis of existing policies (Higman & Pinfield, 2015); how policies are developed and who should be included, including the importance of stakeholders in policy development (Erway, 2013;Shearer, 2015;Tenopir et al, 2017;Van Zeeland & Ringersma, 2017;Verhaar et al, 2017) and the development of policies occurring from the "bottom up" (Lee and Stvilia, 2017;Cruz et al, 2019); tying policy to services, including the relationship between data management policy and services (Higman & Pinfield, 2015); the lack of policy and the need for standards, including discussions on the lack of standards (Briney et al, 2015;Austin et al, 2017); and the lack of research data management policy coupled with the lack of strategic development of these policies (Yu, 2017). Unfortunately, these resources did not provide guidance on how to approach writing our own policy, what has worked for others, what challenges they faced, and how their policy changed over time.…”