minsított

Minsított is a term used in discussions of data privacy and information design to describe a strategy of reducing the amount of personal or sensitive information collected, processed, and shared. The concept is not yet widely standardized and the term appears mainly in academic and practitioner discourse in the 2020s. In its broadest sense, minsított aims to preserve the utility of data while limiting exposure by prioritizing essential information and removing or obscuring the rest.

Practices commonly associated with minsított include data minimization at the source, aggregation and generalization to higher levels of abstraction, pseudonymization or anonymization where feasible, selective disclosure of only necessary attributes, and the use of privacy-preserving analytics such as differential privacy.

Applications span digital services, healthcare, and research, where organizations seek to balance analytical value with user privacy and regulatory compliance. Implementing minsított requires governance: purpose specification, data inventories, impact assessments, and ongoing monitoring to ensure that reductions do not undermine safety or accuracy.

Critics argue that excessive minimization can degrade data quality and impede legitimate uses, and that the term is sometimes used as a rhetorical label rather than a precise methodological framework. Proponents respond that clear privacy-by-design principles and standardized metrics can make minsított a practical toolkit rather than a vague ideal.

See also: data minimization, privacy by design, de-identification, differential privacy, data governance.