The German Informatics Society (Gesellschaft für Informatik e.V., GI) has published a new white paper examining the use of artificial intelligence in research data management (RDM). The paper highlights key opportunities and risks and presents six recommendations for the responsible use of AI in this increasingly important field.
While the use of AI in scientific research is already widely discussed, its implications for research data management have received considerably less attention. Yet AI applications are becoming increasingly relevant throughout the research data lifecycle, from processing and describing data to supporting its discovery and reuse.
The white paper “AI in Research Data Management” addresses this gap. It is based on interviews with six experts involved in Germany’s National Research Data Infrastructure (NFDI). The interviews provide insights into how AI is already being used in RDM and where it could be useful in the future. The paper also looks at how AI may change research infrastructures, the skills researchers need and the way scientific knowledge is produced.
Based on these findings, the white paper puts forward six recommendations:
- Prioritise AI applications where their current benefits are most evident.
- Establish human oversight through a “human-in-the-loop” approach as a guiding principle.
- Develop shared guidelines for documenting the use of AI.
- Invest in controllable and, where appropriate, locally operated AI infrastructure.
- Treat AI literacy as a collective professional development priority.
- Preserve methodological pluralism instead of treating generative AI as the standard solution for every task.
The recommendations are intended to help ensure that AI is used in research data management in a transparent and responsible way, while maintaining human oversight and a diversity of research methods.
The full white paper, AI in Research Data Management, is available here.
