AI in RDM: Navigating the Tension Between Efficiency and Regulatory Clarity

Artificial intelligence is currently transforming many areas of scientific work—including the handling of research data. AI can, for example, support the documentation of datasets, generate metadata, analyse data, or assist in structuring and reusing research data. At the same time, new questions arise regarding data quality, transparency, responsibility, and legal frameworks.

This full-day workshop is aimed at individuals working in research data management or advising researchers in this area who would like to explore the possibilities of AI in RDM in a practical and reflective way.

While the workshop “From Data Chaos to Structure: Critically Using AI in RDM” provides an initial overview of the opportunities and limitations of AI, this advanced format places a much stronger emphasis on practical application.

During the workshop, we will:

• discuss concrete use cases of AI in research data management
• identify typical RDM tasks where AI can provide support
• explore different AI tools and workflows through hands-on exercises
• examine examples from research and RDM practice
• reflect on opportunities, limitations, as well as ethical and legal aspects

Participants will work with concrete examples and exercises in order to develop a better understanding of how AI can be used in a meaningful and responsible way when working with research data.