Data minimization is the principle of collecting, processing and storing only the necessary amount of personal information required for a specific purpose. The principle emanates from the realisation that processing unnecessary data is creating unnecessary risks for the data subject without creating any current benefit or value. The risks of processing personal data vary from identity theft to unreliable inferences resulting in incorrect, wrongful and potentially dangerous decisions.

The principle of data minimization is a global, universal principle of data protection, and can thus be found in almost every legal or regulatory text on data protection/privacy.

• The data minimization principle is the second of the six fundamental privacy principles set forth in the General Data Protection Regulation^[1] and the UK GDPR.^[2]
• The OECD Privacy Guidelines^[3] refer to the data minimization principle as the Collection Limitation Principle (part two, article 7).
• The American Data Privacy and Protection Act (ADPPA), a United States proposed federal online privacy bill that was not enacted included data minimisation as a main principle.^[4]
• The APEC Privacy Framework includes the data minimization principle, referred to as the Collection Limitation principle, as principle III.^[5]
• The American Privacy Rights Act (APRA), a comprehensive data privacy law proposed in April 2024 in the United States, includes a section on data minimisation.^[6]
• The Canadian Personal Information Protection and Electronic Documents Act (PIPEDA) includes the principle as Principle 4 - Limiting Collection ^[7][8].