Building an in-organization research data management training community in an AI-forward world

As technology advances open up new ways of discovering and re-using data, researchers need to be equipped with the skills and knowledge to understand how to adapt these new methodologies to their own scientific discipline, and meet journal and funder data policy requirements. While compliance can help layout these requirements, education is a key tool in showcasing the benefits, opportunities, and importance of good data management throughout the research project lifecycle. Here, we explore the lessons learnt in building a research data management (RDM) training community within our organization, and discuss how interactive engagement with researchers from different career stages can lead to improvements in creating open and FAIR data in the environmental sciences.