Machine actionable DMPs in practice

Data management planning is a key task and an essential element in the process to manage the whole FAIR data life cycle. It is also a mandatory requirement from several major funders, as well as some research organizations, including Chalmers. Yet writing and updating a data management plan - even with the support of a DMP system - is often considered a rather tedious task that, despite the intentions, in the end often fails to return any substantial added value, other than policy compliance, for either researchers or other parties involved. By automating central workflows and involving key stakeholders in that process we have found that it is quite possible to accomplish a solution that not only facilitates the researcher tasks, but also ensures controlled, re-usable metadata and enables central stakeholders to be automatically connected with relevant parts of the process, from planning to sharing and preservation of data. This include identifying issues concerning personal and sensitive data, as well as special or large storage needs, at an early stage in the process. Using the DMP tool Data Stewardship Wizard, funder project databases and not at least the locally developed CRIS system (research.chalmers.se) and supporting locally developed routines, the first steps were implemented in our production workflows (in 2022). This poster presents both the work done so far, as well as ongoing work and planned future developments. We are happy to receive input from participants and to communicate how this could be used to further facilitate the process of making research data open and FAIR.