Supporting Research Data Management with generative AI - a modern FAIRytale?

Interdisciplinary projects pose significant challenges for research data management (RDM). Workflows for generating, processing, and analyzing FAIR data, as well as data formats and supporting infrastructures, are often highly heterogeneous. As a result, unaligned data silos frequently emerge, making data sharing between stakeholders difficult, if not impossible. Moreover, many RDM tasks are complex and are often perceived by researchers as additional, burdensome work. Generative AI offers considerable potential to support tasks in the RDM lifecycle. In turn, well curated and interoperable data can lead to better results when used for training or prompts. In this presentation, we draw on examples from multiple research projects and domains to explore how generative AI can help to address these challenges and support FAIR data practices.