How do anonymization and pseudonymization differ and when should each be applied in MIPC?

• A. Anonymization removes identifying data irreversibly; pseudonymization replaces identifiers with pseudonyms while allowing re-identification under controlled conditions. Use anonymization for analytical datasets; pseudonymization when re-identification is legally or operationally allowed.
• B. Anonymization preserves identities; pseudonymization permanently blocks re-identification.
• C. Anonymization is for operational use; pseudonymization for public data.
• D. They are the same.

Answer: (D)

Anonymization and pseudonymization both aim to protect individuals in data, but they differ in whether re-identification is possible. Anonymization makes all direct identifiers disappear in a way that cannot be reversed, so the data can no longer be linked back to a person. Pseudonymization replaces identifiers with a pseudonym or code, but a separate key or process exists that can map the pseudonym back to the original identity, so re-identification is possible under controlled conditions.

In practice, you’d anonymize data when it will be shared or analyzed publicly or in broad aggregates and there’s no need to identify or re-contact individuals. You’d pseudonymize when the processing still requires the ability to re-link data to individuals under strict governance—such as for follow-up, consent management, or linking with other records—while keeping access to the re-identification key tightly controlled and protected.

So the statement that they are the same is not accurate because one is designed to be irreversible and unlinkable, while the other preserves a reversible mapping under controlled, authorized conditions.