anonymizované

Anonymizovaný is a Czech adjective meaning "anonymized." It describes data, content, or persons from whom identifying information has been removed or replaced so that the individual is not readily identifiable. Anonymizovaný data aim to prevent reidentification, though effectiveness depends on methods and context. By contrast, pseudonymizovaný (pseudonymized) data replace identifiers but can be linked back to individuals with additional information.

Common anonymization methods include removing direct identifiers (names, addresses, IDs), generalization or aggregation (age ranges, regional truncation), masking, data swapping, and adding noise. Some approaches are evaluated using concepts such as k-anonymity, l-diversity, and t-closeness to assess residual reidentification risk. Legal and practical standards vary by jurisdiction.

In the EU, truly anonymized data fall outside the scope of GDPR. Yet achieving true anonymization is difficult, and data believed to be anonymized may still pose risks if combined with other data sources. In Czech practice, anonymizovaný data are frequently used in public datasets and research to enable analysis while protecting privacy.

Examples include anonymized health data for epidemiological studies, anonymized survey responses, and datasets with aggregated statistics that exclude individual-level identifiers.