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Swiss Data Anonymization Center

Anonymization, proven by research.

We develop, validate, and openly publish methods that let data be shared without exposing the people behind it.

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Patient register · n = 25,000 live
Before anonymisation 28% High risk
0%100%
After anonymisation 2.4% Safe
0%100%

risk ↓ 91% · utility preserved · computed in-browser

sdcMicro on CRAN since 2007
Peer-reviewed papers 90+
Flagship grant SNF Bridge
Peer-reviewed in the Journal of Statistical Software JSS
What we do

Three ways we move the field

Research

Funded projects, open methods

SNF-funded projects, peer-reviewed publications, and open-source software anyone can audit.
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Courses

Training that transfers

Open courses and in-house training in anonymization and synthetic-data methods.
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For companies

Defensible data sharing

Consulting, synthetic data, and independent audits of your anonymization pipelines.
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The method, in the open

Every claim we make is one you can re-run.

Risk is measured, not asserted. We publish the methods, the code, and the evidence — so reviewers, funders, and partners can check the work themselves.

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k-anonymity sweep utility preserved
Raw microdata 42% High risk
0%100%
Generalised (k = 3) 11% Caution
0%100%
Generalised (k = 5) 2.4% Safe
0%100%