Introduction to data anonymization

This workshop addresses the basics of data anonymization, data synthetization, disclosure risk and data utility after anonymization

The workshop deals with the introductory basics of data anonymization of quantitative data, but also shows alternative data anonymization based on data synthesis. In addition, the problem for anonymization of qualitative (text) data will be outlined. This course is about anonymization and not about pseudo-anonymization (pseudonymization) using encryption methods. The latter does not solve the problem of data protection.

The course gives an overview of data anonymization methods but does not leave out how to measure disclosure risk – the second most important task before and after applying anonymization methods. We also discuss data utility, the most important part of data anonymization, as anonymization is about providing anonymized data with high data utility. Participants will gain an awareness of data attack scenarios, the sensitivity of data and the exploratory nature of data anonymization. Participants are made aware that the choice of anonymization methods depends on many parameters and is case-dependent. Data stewards will know when data anonymization support is needed, what disclosure control methods are available and where to find additional information and services to sufficiently ensure a low disclosure risk of personal data in a research project while maximizing data utility.

Trainer: Prof. Dr. Matthias Templ (FHNW)

Workshop language: English

Data stewards and other members of the university's RDM network will be invited to this course by email. Other people who are interested in taking part in the course are asked to contact the coordinators of the Data Stewardship Programme.

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