Train-the-Trainer Concept on Research Data Management

This version of the 'Train-the-Trainer Concept on Research Data Management' is the English translation of the fifth updated version of the German 'Train-the-Trainer-Konzept zum Forschungsdatenmanagement'. The translation of the concept resulted from the need to address the ongoing internationalisation of science in Germany and the fact that researchers are increasingly communicating in English. Building individual skills in research data management and training multipliers in English is therefore becoming even more important. Due to the existence of the National Research Data Infrastructure (NFDI) with its subject-specific consortia, the newly approved Clusters of Excellence and Collaborative Research Centres, the need for qualified staff is growing immensely. This also applies to universities and research institutions in general. For this version, the content of all units has been revised and experiences acquired from previous online Train-the-Trainer Workshops have been integrated into the concept. This concept thus provides new, more detailed information for already experienced Research Data Management (RDM) professionals. This train-the-trainer concept addresses RDM topics in an inspirational way and delivers teaching methods at the same time. Furthermore, topics such as diversity and barrier-reduced teaching materials are addressed to create an engaging learning environment. Please note that some of the content and included materials cover specific issues that only apply to the German science community. We hope that readers of this translated version of the concept will receive useful and informative insights in the field of research data management.

Acknowledgements:
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 101035821 (EUniWell #Research).
Kindly take note that this document was translated with the technical services of ChatGPT and was adapted in terms of language based on native speaker proofreading by Andrew Rennison.