Data Management Plans: a Resource to Shape Institutional Data Management Services

Abstract

At KU Leuven, a university in the Flemish region of Belgium, data management plans have become an important resource to drive and shape the development of data management support, services, and training. With 8,000 researchers and 7,000 PhD students in fundamental and applied research across a comprehensive range of disciplines, KU Leuven is the largest university in Belgium. Public research funding is provided by the federal and regional governments, mainly via the Research Foundation Flanders (FWO) and via research funding allocated to universities based on excellence criteria through the Special Research Fund (BOF) and the Industrial Research Fund (IOF).

Since 2018, FWO and BOF-IOF incorporated data management into their policies, requiring researchers to submit Data Management Plans (DMPs) to their institutional research office. Since then, the number of DMPs that are developed each year has increased exponentially, from 150 in 2018 to nearly 700 per year now. The Research Coordination Office at KU Leuven decided to review all DMPs to provide feedback to ensure high-quality plans. To manage the submission, monitoring, review, and preservation of this volume of DMPs efficiently, an online platform was developed that is integrated with the university’s research information systems.

Initially, the focus of the DMP review was on supporting the development of DMPs, as this was a new concept for researchers. The review process has significantly improved the quality of DMPs. Later, support shifted to provide advice on best practices in data management. Reviews of over 2600 DMPs provide a rich source of information to develop services and training. Based on findings from DMP reviews, the IT department developed an interactive storage guide; ethical and legal compliance in research projects can be monitored; new data management training modules are developed; and a collection of example DMPs has been developed. In addition, the growing DMP collection is a rich source of information on researchers’ data practices, providing the baseline information to develop further services. Future plans include implementing artificial intelligence in DMP reviews to automate problem detection and exploring machine-actionable DMPs for an institutional data register.