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Special Categories of Data Under the GDPR: Practical Guide

What are special categories of data?

Special categories of data are personal data that, because of their nature, may seriously affect a person’s privacy, equality or freedom. Article 9 GDPR starts from a strict rule: processing is prohibited unless a specific exception applies and appropriate safeguards are in place.

This category includes data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, genetic data, biometric data used to uniquely identify a person, health data and data concerning sex life or sexual orientation.

Why these data require extra care

The distinction is not merely technical. Processing health data, biometric identifiers, ideology or trade union information may create risks of discrimination, workplace exclusion, loss of confidentiality or reputational harm. For this reason, it is not enough to rely on an Article 6 GDPR lawful basis: the controller must also rely on a valid Article 9 exception.

Common Article 9 GDPR exceptions

Common exceptions include explicit consent, employment and social security obligations, vital interests, occupational medicine, public health reasons, substantial public interest or the establishment, exercise or defence of legal claims.

The Spanish Data Protection Authority explains that the general rule is prohibition and that exceptions must be assessed carefully. In practice, companies should document which exception applies and why the processing is necessary.

Practical measures for companies

Before processing special category data, an organisation should confirm whether the data are truly necessary, restrict internal access, define retention periods, apply stronger security measures and assess whether a data protection impact assessment is required. It should also provide clear information to individuals, especially where the purpose is sensitive.

Frequent examples

In short, special categories of data cannot be treated as ordinary personal data. They require stronger justification, a specific purpose and compliance measures showing that the organisation has properly assessed the risk to individuals.

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