Strengthening Data Management Systems: Insights from the Machine Actionable Plans (MAP) Project's Institutional Pilots

Data Management and Sharing Plans (DMSPs) are typically viewed only as a requirement researchers must meet as part of grant proposals to funding agencies; machine actionable DMSPs (maDMSPs) offer the potential to enhance the value of research data produced at institutions by making it more discoverable and connected to other parts of the research ecosystem. In recent years, maDMSPs have emerged as key mechanisms for the United States federal funding agencies’ policies for public access to research data. This paper provides overviews and insights from four institutions that were part of the Machine Actionable Plans (MAP) Pilot Project with the goal to develop projects related to maDMSPs. The case studies cover using generative AI for DMSP feedback, organizing a cross-campus workshop on maDMSPs, attempting to track and connect campus systems related to grant-related research, and creating a proof-of-concept for networked RDM and DMSP workflows. Finally, this paper concludes by acknowledging the rapid changes happening in federal funding agencies in the United States, highlighting potential failure points, and emphasizing the importance of staying up to date with changes to US federal policies.