RDM - An Online Introduction: A learning module developed by HeFDI

Traditional face-to-face teaching is increasingly being supplemented by hybrid or fully digital formats. The federal state initiative Hessian Research Data Infrastructures (HeFDI) embraces this trend by offering online learning materials as open educational resources (HeFDI Data OER). The learning module "Research data management - an online introduction" is part of this offer and provides easily accessible knowledge about basic topics of research data management (RDM). After it was first published in German in 2022, it was recently made accessible in English to make sure that a wider RDM-interested audience can benefit from it. This contribution aims to present the structure and content of the learning module for potential users as well as people providing RDM support who want to expand their portfolio of learning resources. Import files of the learning module are available for the learning platforms Moodle and Ilias and include multimedia content such as text, pictures, charts, and videos. The covered topics are structured as chapters that have a modular design which means that they build on each other thematically but can also be worked on individually. Every chapter is rounded off by summarizing handouts and test questions. The topics include an introduction to RDM, information about the life cycle of research data, data management plans, the FAIR and CARE principles, metadata, data quality, data organization, data archiving and publishing as well as legal aspects. It is implemented at every university in HeFDI and has proven suitable for acquiring RDM knowledge both in a self-studying as well as curricular teaching context. It was developed to fit the needs of hybrid teaching formats (such as flipped classrooms) or fully digital offers is targeted towards students, doctoral candidates and researchers who are looking for an easy-to-understand introduction to RDM. Other universities outside of Hesse have already integrated the module into their learning platforms as well. Furthermore, it was also adapted by NFDI4Biodiversity as a self-study unit that provides essential domain-specific knowledge in research data management and addresses both students and researchers in the field of biodiversity and environmental sciences. We strongly encourage further reuse, are particularly interested in additional subject-specific adaptations by other NFDI consortia and can offer support with the technical implementation of the learning module. All in all, it can be used to easily integrate RDM and data literacy into universities' teaching portfolios. Furthermore, especially with subject-specific expansions, the data stewards of tomorrow can be trained at an early stage of their career.