Data Anonymisation and Security for Open Data

Open Data creates opportunities for transparency, innovation, research, and better public services. At the same time, publishing data responsibly requires careful attention to anonymisation and security. Developed in the context of the EU project Data Opener Central Europe (DoorCE), this course introduces the key concepts, risks, and practical decisions involved in preparing data for open publication, especially for public authorities, municipalities, data stewards, coordinators, managers, IT and security staff, and Open Data practitioners.

Participants will learn why anonymisation is more than removing names, how re-identification can happen through indirect identifiers or combinations of variables, and how anonymisation differs from pseudonymisation and data security. The course also introduces the European legal and governance context, including the relationship between GDPR, anonymised data, and responsible Open Data policies.

Through practical examples, quizzes, and exercises, learners will explore common risk factors in public sector datasets and core anonymisation methods such as suppression, masking, aggregation, and generalisation. The course also covers basic security practices, including access control, secure storage, encryption, and common human mistakes.

By the end of the course, participants will be able to identify re-identification risks, apply appropriate anonymisation approaches, and make informed decisions about whether data should be published openly, shared with restrictions, aggregated, or not published.