2nd Forum Helmholtz Research Data Commons: Enhancing Research Data Workflows for and with AI

Tuesday 30 Sept 2025, 10:00 → 12:00 Europe/Berlin

Zoom (online)

The Helmholtz Metadata Collaboration (HMC) and the Helmholtz Open Science Office invite you to the second iteration of the Helmholtz Research Data Commons on September 30, 10:00 to 12:00 CEST, this time focussing on: Enhancing Research Data Workflows for and with AI. In this online event, colleagues from the AI team at the Jülich Supercomputing Center will provide practical insights into preparing research data for AI and showcase their AI tool BLABLADOR, a free and privacy-aware Helmholtz AI LLM service, and its possible applications in research data analysis. The event will include an open discussion round on the topic with the speakers, which everyone is invited to participate in.

For participation, please register here.

Research Data Commons is a joint recurring Helmholtz-forum for the exchange and discussion of research data-relevant topics at Helmholtz, initiated in 2024 by the Helmholtz Metadata Collaboration (HMC) and the Helmholtz Open Science Office. The events are open to employees from all Helmholtz centers to share their experiences and approaches around specific focus topics.

10:00 → 10:10 Welcome and Introduction

Speakers: Mathijs Vleugel (Helmholtz Open Science Office), Sören Lorenz (Helmholtz Metadata Collaboration)

10:10 → 11:00 Talks and Presentations

Convener: Marc Lange (Helmholtz Open Science Office)

10:10 Is Your Data Ready for AI? A Practitioner‘s Perspective

Speaker: Stefan Kesselheim (Forschungszentrum Jülich)

10:25 BLABLADOR – The experimental Helmholtz AI LLM server

Speaker: Alexandre Strube (Forschungszentrum Jülich)

10:35 Use Case: LLM Applications in Ground-Based Gamma Astronomy

We present a multi-agent application for next-generation Cherenkov Telescope Array Observatory, designed to automate the generation of Pydantic Python models directly from free-text descriptions or structured files. It also explores the use of the multi-agent framework AutoGen, as well as minimal function tools available in new OpenAI interfaces, incorporating a feedback loop to verify and refine generated code before user presentation, streamlining the workflow for astrophysical data management. The app is baked with Blablador's GPT-OSS, as the best performing model for the task out of selected models.

Speakers: Elisa Jones (DESY), Dmitriy Kostunin (DESY)

10:45 Q & A

11:00 → 11:50 Discussion – Enhancing Research Data Workflows for and with AI

11:50 → 12:00 Closing