Data Management Plans (DMPs) are required increasingly to be submitted alongside ethical approval and funding applications for research projects, requiring researchers to consider what data will be produced as part of their research and how that will be managed and stored going forwards. These are typically managed in separate siloed systems, and stored in unstructured formats (eg. PDFs). Recording a DMP in a structured “machine-actionable” format enables systems to report and act on the planning information held within these documents. In this session we will examine how DMPs can be structured in a machine-actionable way, and explore some of the benefits of managing them in the repository alongside dataset deposit and management features. This will include discussion of the challenges in adapting institutional and funder forms to map to a machine-actionable data model, and the use of the RDA Common Standard for machine-actionable DMPs. The implementation of machine-actionable DMPs in Haplo Repository will be used as a case study. We will look at “quick wins” for attendees looking to implement maDMPs in their institutions, as well as consider some of the possible longer term benefits this approach enables.