anonymiseras

Anonymiseras is the Swedish passive form of anonymisera, meaning that data or records are made anonymous. It refers to the set of techniques used to transform personal data in such a way that individuals cannot be identified, directly or indirectly, by reasonable means. The goal is to reduce privacy risks while preserving data utility for analysis and reporting. Anonymisation is distinct from pseudonymisation, where data can still be linked to an individual with additional information; anonymised data should not be reversible.

Common methods include removal of direct identifiers (names, national identity numbers, addresses), aggregation or generalisation (e.g., age in ranges, geographic areas), suppression of small groups, data masking, and data perturbation. Advanced approaches draw on statistical and mathematical techniques such as k-anonymity, l-diversity, t-closeness, and differential privacy. The choice of method depends on the data type, the intended use, and the assessed risk of re-identification.

Legal and ethical context: Under the EU General Data Protection Regulation (GDPR), personal data are subject to protection; truly anonymised data are not considered personal data. However, achieving true anonymisation is challenging, and re-identification risks can remain, particularly when data are combined with external sources.

Applications and challenges: Anonymiseras enables data sharing for research, statistics, or service improvement while reducing privacy concerns. A challenge is balancing data utility with privacy risk; over-anonymisation can render data less useful, while under-anonymisation increases risk.

Related concepts include de-identification, pseudonymization, and privacy-preserving data analysis techniques.