Mittepersooniline

Mittepersooniline is a term encountered in privacy studies to describe data attributes that are not identifying on their own but can contribute to identification when combined with other information. It is used to characterize a gray area between non-identifying data and personal data, emphasizing the potential re-identification risk present in certain data combinations.

Etymology and usage: The word appears to be a compound blending elements suggesting middle or mid-level personal data. The concept is described in discussions on data governance as a way to capture attributes that are not inherently identifying but acquire identifying power in linkage scenarios.

Definition and characteristics: Mittepersooniline attributes are context-dependent and typically require linkage with additional datasets or attributes to reveal identities or sensitive traits. They are not standalone identifiers, but their risk profile rises in data-sharing, cross-dataset analyses, or advanced analytics. This makes them particularly relevant for risk assessment, anonymization planning, and privacy-by-design considerations.

Examples: Coarse geographic indicators (such as city-level location), broad age ranges, or device-type categories can be seen as mittepersooniline when paired with other data. Hashed identifiers or pseudonymous data may also fall into this category in certain contexts if additional attributes enable re-identification.

Policy implications: There is no formal, universally adopted legal category named mittepersooniline in major privacy frameworks. Nonetheless, the concept informs practical risk assessments, data minimization, access controls, and consent design, guiding organizations to treat certain linked attributes with heightened caution during data sharing or processing.

See also: quasi-identifiers, de-identified data, re-identification risk, privacy-by-design, differential privacy. History of the term is informal and varies by discipline; it remains a topic of theoretical and practical discussion rather than a standardized category.