Ickeidentifierbar

Ickeidentifierbar is a Swedish adjective used to describe data, information, or situations that cannot be used to identify a specific person. In privacy and data protection discourse, data labeled as ickeidentifierbar should be free from enough identifiers or quasi-identifiers that would allow re-identification, even when combined with other available information.

In practice, achieving ickeidentifierbar data involves de-identification or anonymization techniques. Common approaches include aggregation or generalization of attributes, removal or masking of direct identifiers, and the addition of controlled noise. More formal concepts related to this goal are k-anonymity, l-diversity, and, in some contexts, differential privacy, which provide frameworks for reducing re-identification risk while preserving data utility.

The term is primarily used in Swedish-language texts and policy discussions. It reflects a standard objective in data publishing, research, and public administration: to balance data utility with the protection of individuals’ privacy by ensuring that released data cannot be used to identify identifiable persons.

Limitations and challenges remain. True ickeidentifierbar data is difficult to guarantee, especially when datasets can be linked with other sources. Even anonymized data can pose re-identification risks if auxiliary information is available. Consequently, ongoing risk assessment and privacy-preserving techniques are essential when sharing or releasing datasets.

See also: data anonymization, de-identification, privacy-preserving data analysis, differential privacy, re-identification risk, GDPR and anonymization.