Glossary
Glossary of anonymization and data protection terms
Practical definitions of the concepts you meet when documents have to be anonymized or pseudonymized: what the GDPR says, how the ICO and EU regulators read it, and what it means for a case file, a court judgment or a spreadsheet.
Glossary
Anonymisation: when personal data stops being personal
Anonymisation is the process of turning personal data into information that no longer relates to an identifiable person, taking into account all means reasonably likely to be used. Truly anonymous data falls outside the UK and EU GDPR.
ReadSpecial category data: health, union membership, criminal offence data and more
Personal data that Article 9 of the UK GDPR and EU GDPR bans processing except in listed cases: health, ethnicity, politics, religion, union membership, genetics, biometrics, sex life or orientation. Criminal offence data falls under Article 10.
ReadDocument redaction: definition and how to get it right
Redaction is the permanent removal of selected content (a name, an account number, a signature) from a document before it is shared, so that it cannot be recovered from the text, the images or the hidden data of the file.
ReadGDPR Recital 26: where personal data ends and anonymous data begins
Recital 26 of the GDPR explains how to decide whether a person is identifiable: by considering all means reasonably likely to be used to identify them. If they are not identifiable, the information is anonymous and the GDPR does not apply.
ReadPersonal data: what it is and where it hides in your documents
Personal data is any information relating to an identified or identifiable living person, directly or indirectly: a name, an ID number, a number plate, a signature or a set of details that together reveal who someone is.
ReadData protection impact assessment (DPIA)
A DPIA is the assessment a controller must carry out before processing that is likely to result in a high risk to people's rights and freedoms: describe the processing, test its necessity, assess the risks and set out measures to reduce them.
ReadK-anonymity: definition, worked example and its limits
K-anonymity is a property of a dataset in which every combination of quasi-identifiers (postcode, age, sex…) appears in at least k records, so no individual can be distinguished from at least k−1 others.
ReadDocument metadata: definition, risks and how to clean it
Metadata is the data a file keeps about itself: who created it, when, with which software, how it was edited and, for photos, even where it was taken. It does not appear on the page, but it travels with the file.
ReadData minimisation: share only what is needed, documents included
Data minimisation is the principle in Article 5(1)(c) of the UK GDPR and EU GDPR that personal data must be adequate, relevant and limited to what is necessary for the purposes of processing.
ReadRe-identification: how “anonymous” data points back to people
Re-identification means attributing data that was believed to be anonymous or pseudonymised to a specific person again, usually by matching it with other sources through quasi-identifiers or contextual details.
ReadPseudonymisation: replacing identities without losing the thread
Pseudonymisation processes personal data so it can no longer be attributed to a person without additional information that is kept separately and protected. It is reversible, so pseudonymised data remains personal data.
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