What we've built and for whom — SwissAnon's funded research, Matthias Templ's earlier client engagements, and the partners we work with.
SwissAnon's own funded research.
SNF Bridge Discovery What we didOur flagship project: privacy-preserving methods for event and longitudinal data — masking trajectories, protecting event histories, and pushing re-identification-risk assessment beyond k-anonymity.
ImpactOpen, reproducible tools that let organisations analyse and share data following the same people over time, with quantified risk.
Nestlé What we didTwo ongoing engagements under the EU GDPR/EDPB framework. Using a completed study as the worked example, we show the team what anonymization can achieve and how to make the decisions it requires. In parallel, we anonymize the data of a clinical study before the identifiable original is deleted.
ImpactA team that can make anonymization decisions itself, and study data that stays usable after the original is gone, with the measurements that carry the scientific value preserved.
SBB What we didHousehold-level anonymization and geographic protection of SBB's 9-million-person Synthetic Population (SynPop), with a formal disclosure-risk assessment for a differentiated data-release policy.
ImpactIndividual-level population data that can be shared and used safely in agent-based transport models — not the current all-or-nothing.
Anonymization and synthetic-data projects delivered before SwissAnon was founded:
World Bank What we didAnonymised census and survey microdata and delivered statistical-disclosure-control training; earlier, rebuilt the sdcMicro graphical interface and developed synthetic-data methods for safe microdata dissemination.
ImpactEnabled national statistical offices to share census and survey data with measured, controlled re-identification risk.
Eurostat What we didDelivered statistical-disclosure-control tooling and synthetic-data generation methods under Eurostat special grant agreements.
ImpactStrengthened the open methods European statistical authorities rely on to release microdata safely.
What we didDeveloped synthetic-data and disclosure-control methods and trained statistical offices in developing countries, with the OECD/PARIS21 and the International Household Survey Network.
ImpactHelped resource-constrained statistical offices adopt reproducible, open-source anonymisation in routine data dissemination.
What we didAnonymised sensitive health-insurance data so it could be analysed and shared without exposing individual policyholders.
ImpactLet a major Swiss health insurer put its data to work within strict privacy constraints.
What we didAnonymised mobility and trajectory data — among the hardest data to protect, because movement patterns are highly identifying.
ImpactMade location-data analysis possible without leaving re-identifiable traces of individuals.
What we didAnonymised smart-meter energy-consumption data.
ImpactEnabled energy-usage analysis while protecting identifiable household-level patterns.
