Abstract

Interoperability, i.e., the possibility to combine information generated in different contexts and across different platforms, is a key request in the general framework of Open Science and FAIR data [1]. This should also be done for project-related information collected in the form of Data Management Plans (DMPs). In contrast to free-text DMPs, machine-actionable DMPs (maDMPs) provide a machine-readable format that allows for automated processing and integration into different platforms.

To facilitate interoperability, the Research Data Alliance DMP Common Standards Working Group suggested a minimum set of application-independent fields for maDMPs [2]. At the same time, some DMP platforms, such as RDMO [3] and DataPLAN [4], define DMPs as structured objects composed of fine-grained fields, which allows further comparison and mapping between them and facilitates potential interoperability.

In our workgroup, we intend to implement the subsequent steps towards DMP interoperability, starting with the two platforms used in the NFDI context, RDMO and DataPLAN. Our initial task, which began at a three-day hackathon in October 2024, is aligning the given DMP data models to each other [5], similar to previous work on the alignment of software management plans [6]. In the following, we will check the capability of each software to import/export information according to one of the other data models. Our test use cases will be a generic DMP and a DMP for life sciences.

Our work will help design DMP infrastructure and templates to be interoperable from the beginning. We plan to work together with the developers of DMP platforms to extend their functionalities and with authoritative community initiatives such as the Research Data Alliance.

We are optimistic that with this baseline, further implementations will take place, benefiting all instances and tools that rely on RDMO, the NFDI Consortia, and the wider community, allowing the extension of this work towards other disciplines and advancing towards maDMPs.