This workshop focuses on entire work processes with AI in research data management. Participants distinguish between AI assistants, automated workflows, and more autonomous systems, and develop criteria for determining which tasks in research data management can be automated and in which areas human oversight remains essential.

Contents:

• AI assistants, workflows, agents, and agent-based systems

• Appropriate and inappropriate automation scenarios in FDM

• Human-in-the-loop and boundaries of responsibility

• Bias and responsibility

• Data protection and handling of sensitive research data

• Copyright, scientific integrity, and the EU AI Act

• Documentation of AI usage and traceability

• Development of custom use cases

Learning Objectives:

Participants will be able to…

• distinguish between AI assistants, automated workflows, and more autonomous AI systems,

• evaluate FDM tasks in terms of their suitability for AI support and automation,

• identify risks related to data protection, bias, scientific integrity, and accountability,

• develop appropriate forms of AI support for their own FDM use cases, including necessary human checkpoints.

Registration form (deadline: 20.11.2026)