Data minimisation
Data minimisation is the principle in Art. 5(1)(c) GDPR that personal data must be adequate, relevant and limited to what is necessary in relation to the purposes for which they are processed. It requires the controller to ask, for each data element, whether the purpose can be achieved without it, with less of it, or with a less identifying version of it.
The principle applies at every stage: design of a protocol and eCRF (collect only variables the statistical analysis plan needs), choice of identifiers (subject codes rather than initials and full dates of birth), configuration of apps and devices (no unnecessary permissions or background collection), and retention (delete or anonymise once the purpose is fulfilled). It is a core component of data protection by design and is expressly reinforced for high-risk AI systems by the data governance requirements of the EU AI Act.
Minimisation is regularly tested by regulators in clinical research: collecting full birth dates when age suffices, free-text fields that capture unnecessary detail, or copying entire medical records into a research database are frequent audit findings. It should be documented in the DPIA and revisited whenever a protocol amendment adds new data points.
