Supporting organizations in evaluating, designing, and applying anonymization for safe data reuse.
Organizations want to use data. Privacy requirements make it complex.
Organizations increasingly rely on data for research, AI, and innovation.
However, sharing or using data often involves significant privacy risks.
Simply removing names or direct identifiers is rarely sufficient.
Even datasets that appear anonymized may still allow individuals to be re-identified.
Understanding and mitigating these risks requires specialized expertise.
Pharma & diagnostics
companies
Several global pharma and
healthtech companies
• Strengths and weaknesses
• When to use which approach
• Limitations of tools
Paper – Understanding Anonymization,
De-identification and Pseudonymization.
Independent expert in data anonymization and re-identification risk.
Specialized in evaluating privacy risks in datasets used for research, AI, and data sharing.
Focus on scientific analysis and
independent advice.
Renate van Kempen
For privacy professionals, security experts, and anyone interested in learning more about anonymization.
23 September 2026
17.00-18.00 CEST
Dataset intake and context analysis
Identification and classification of identifiers
Re-identification risk modelling
Evaluation of possible transformations
Final risk assessment & recommendations
Audit-ready report
If you are planning to share, publish, or use personal data,
understanding the privacy risks is essential.
