Workshop Series "AI in Research Data Management: Balancing Efficiency and Responsibility"

Three-part online workshop series on November 10, 17, and 24, 2026 on practical and responsible AI use in research data management.

The three-part workshop series “AI in Research Data Management: Balancing Efficiency and Responsibility” will take place online on November 10, 17, and 24, 2026. It is aimed at researchers, teaching staff, doctoral candidates, and research support staff within the Berlin University Alliance who already have a basic understanding of research data management.

The series focuses on the use of generative AI and large language models in research data management. It combines technical foundations, practical applications, and critical reflection on issues such as reliability, data protection, scientific integrity, and accountability. Participants will explore different AI tools and use cases and develop criteria for meaningful and responsible AI use in their own work.

The first workshop introduces generative AI and its potential for research data management. The second focuses on practical work with structured tasks, information processing, hallucinations, and quality assurance. The final session examines AI-supported workflows, agents, automation, human oversight, data protection, copyright, scientific integrity, and the EU AI Act.

Dates: November 10, 17, and 24, 2026
Time: 10:00–11:30 AM each day
Location: Online
Organizer: Berlin University Alliance
Instructor: Dr. Katarzyna Biernacka, rti-studio
Language: English
Admission: Separate registration required for each workshop
Registration deadlines: November 1, November 10, and November 20, 2026
Audience: Researchers, teaching staff, doctoral candidates, and research support staff at the Berlin University Alliance
Prerequisite: Prior knowledge of the fundamentals of research data management
Focus: Generative AI, LLMs, research data management, context engineering, quality assurance, AI agents, automation, data protection, and scientific integrity
Special feature: Three-part series combining technical, practical, and responsible AI perspectives
November 10: Understanding AI and Using It Effectively for Research Data Management
November 17: Working with AI in Research Data Management
November 24: Responsibility and Application of AI to Research Data Management Practice