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As highlighted in ENAR’s work, equality data can support better policy design and accountability when collected responsibly. At the same time, collecting identity data can conflict with commitments to privacy and autonomy, especially where autonomy includes the ability to decide how, when, and whether to participate.

This tension can be addressed by grounding data practices in principles that support self-determination and recognise that agency must be intentionally enabled: 

• Self-identification: Information about ethnic or racial background should rely on how individuals define themselves. No one’s identity should be assigned externally or inferred without their input.

• Voluntary participation: Providing equality-related data must always be optional. Individuals choose whether to participate, and no collective agreement is required for data collection to proceed. Refusing to share information must never result in penalties, reduced access to services, or loss of benefits.

• Data confidentiality and protection: Sensitive information must be handled with strict confidentiality. Secure processes should ensure that data are anonymised as early as possible and safeguarded against misuse.

• Informed consent: Participants must receive clear and accessible information about why the data are being collected, how they will be used, and any potential risks or benefits. Data should only be processed for the stated purpose and not shared beyond it. Consent must be explicitly and freely given.

• Community involvement: People and communities affected by discrimination should be meaningfully involved at every stage of the process, from defining categories to analysing findings and sharing results, either directly or through representative organisations.

• Recognition of multiple and intersecting identities: Individuals should be able to identify with more than one category. Data frameworks should allow for intersectional analysis that reflects the complexity of lived identities.