Successful skills transfer requires that learning objectives are defined in such a way that they accurately describe the intended learning gain. For this purpose, the Learning Objective Matrix (LOM) for the teaching of Research Data Management (RDM) was developed. The matrix formulates learning topics and objectives for all RDM-relevant skills for four different target groups: Bachelor’s and Master’s students, early career researchers, and Data Stewards. In the present third version, in addition to new and revised content and learning objectives, extensive accompanying material has been developed, including application scenarios, a how-to-use-guide, and a glossary of terms used in the matrix. The glossary contains more than 40 terms and is unique in its scope in the field of RDM. The present article shows practical applications of the LOM for planning RDM training in academic libraries. We discuss how different actors and stakeholders can benefit from the LOM. We identify how the learning objectives can be applied to different target groups and how the levels of competence differ. We show, ultimately, the potential of the LOM for academic libraries and beyond to bring about a further development of RDM competences to the academic community.

This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution will be published in the conference proceedings of the 9th European Conference on Information Literacy, ECIL 2025, Bamberg, Germany, 22nd - 25th September.