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...

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...