Participants appreciated the positive atmosphere, inspiring presentations, open discussions, and excellent organization. One attendee summarized:
“I liked learning about new methods, seeing how others handle their data challenges, and understanding that we can all benefit from sharing our tools, even if they seem very specific.”
Day 1: Setting the stage and community dialogue
The forum began with a keynote address by Marco Salvalaglio (TU Dresden) on integrative approaches to modeling and tailoring material microstructures. The afternoon session covered data infrastructures, semantic tools, and interoperable workflows. This session was complemented by a discussion on simulation data.
In the evening, the demonstrator session allowed participants to explore tools and workflows firsthand — a highlight for those new to RDM. One participant commented, "As someone who has not had much to do with research data management, it was a good opportunity to see use case demonstrations, especially about electronic lab notebooks.“
Day 2: Workflows, digital transformation, and posters
The second day began with a keynote address by Özlem Özcan (BAM) on the autonomous exploration of alloy chemistries using a materials acceleration platform. Throughout the day, talks and discussions covered workflows for FAIR data, digital lab notebooks, and the semantic integration of experimental and microstructure data.
A poster session during lunch provided an opportunity for further networking and informal exchange. The day concluded with a session on community-driven priorities for future NFDI-MatWerk activities and a shared dinner for registered participants.
Day 3: AI and Machine Learning in RDM
On the final day, the focus was on the role of AI and machine learning in RDM. There were two keynote speakers: Norbert Huber (BAM) discussed ML-driven materials engineering, and Benjamin Wahlmann (FAU) discussed numerical alloy design through optimization and ML. Presentations and discussions explored how large language models, ontologies, and ML-based workflows can transform materials science and engineering (MSE) data practices.
The forum concluded with a closing discussion that reinforced the community’s shared ambition to make FAIR data principles actionable and impactful in everyday research.
For NFDI-MatWerk, this exchange came at just the right time: in the run-up towards a possible second funding phase, the insights gained in Siegburg provide valuable orientation for understanding the needs and priorities of the community more clearly. These impressions and discussions will directly inform the upcoming proposal and help shape the consortium’s future activities in a way that aligns with the community’s expectations.
Picture Gallery: https://nfdi-matwerk.de/nfdi/2025/symposium/picture-gallery