Avidentifiering

Avidentifiering, also known as data de-identification or anonymization, is the process of removing or altering personally identifiable information (PII) from datasets so that the individuals to whom the data relates cannot be identified. This is crucial for protecting privacy while still allowing for data analysis, research, and sharing. The goal is to transform data into a state where re-identification of an individual is either impossible or extremely difficult.

There are several techniques used in avidentifiering. Masking involves replacing specific data points with generic characters or symbols. Generalization reduces the precision of data, for instance, by replacing an exact age with an age range or a specific location with a broader geographical area. Suppression is the removal of entire data fields that are deemed too sensitive. Pseudonymization replaces direct identifiers with artificial identifiers or pseudonyms, allowing for re-identification if the key linking the pseudonym to the original identity is retained, but not generally accessible.

The effectiveness of avidentifiering depends on the specific techniques used and the context of the data. It is important to consider the risk of re-identification, especially when combining de-identified data with other available information. Regulatory frameworks like GDPR and HIPAA often mandate or strongly recommend avidentifiering practices to ensure data protection and privacy compliance. The ongoing evolution of data analysis techniques necessitates continuous review and improvement of avidentifiering methods.