On January 26, 2026, the SwissAnon Competence Center hosted a one-day workshop bringing together 19 professionals from Switzerland and across Europe. Participants from public health agencies, statistical offices, universities, data protection authorities, healthcare providers, and private sector organizations joined us for intensive training in data anonymization and synthetic data generation.
This workshop embodies the core goal of our SNF Bridge project: translating cutting-edge research into practical skills that professionals can immediately implement. The day covered essential anonymization techniques including microaggregation, local suppression, recoding, noise addition, and PRAM (Post Randomization Method), alongside risk assessment using real-world examples.
The centerpiece was hands-on training with the R package sdcMicro—a research output that has become an industry standard. Rather than just learning theory, participants worked through actual datasets, configuring projects, applying techniques sequentially, and experiencing the critical privacy-utility trade-offs firsthand. This practical focus ensured everyone left with capabilities they could deploy in their own organizations.
We also introduced cutting-edge methods at the frontier of anonymization research: statistical synthesis, GAN-based synthetic data, and LLM-based generation. These sessions sparked rich discussions about how AI technologies might transform data sharing, with conversations continuing into the apéro where participants exchanged experiences and explored potential collaborations.
The strong international interest—with participants traveling from across Europe—confirms the urgent need for practical anonymization expertise. We’re already planning our next workshop and invite practitioners to share what challenges and topics you’d like us to address.
Workshop materials are available on GitHub for participants.