From FAIR Data to Actionable Knowledge: Generative AI in Research Data Management
Research data management (RDM) is increasingly challenged by the volume, heterogeneity, and complexity of data generated across scientific disciplines. Recent advances in generative AI offer new opportunities to support researchers in organizing, enriching, and reusing research data more effectively.
From FAIR Data to Actionable Knowledge: Generative AI in Research Data Management
- Sandra Geisler (RWTH Aachen University)
This talk explores how generative AI can enhance the research data lifecycle and support key RDM processes. Particular attention is given to semantic annotation as an important enabler for FAIR data practices exemplified with KONDA, a tool that leverages generative AI to support the identification and generation of domain-specific metadata based on ontological concepts.
The presentation further highlights practical use cases from medicine, materials science, and manufacturing, demonstrating how AI-enhanced methods and tools can improve data management, facilitate interoperability, and enable data-driven applications across diverse scientific domains.
All presentations by the speakers will be published via the FDM.SH Zenodo Community.
No registration is required – we look forward to your participation!