Consentshape

Consentshape is a conceptual framework used in privacy engineering to express and visualize user consent preferences for data processing. It combines a data-model representation with a geometric visualization, mapping consent attributes to elements of a shape. The term is discussed in privacy research and in experimental privacy management tooling to explore how users and systems can understand and govern consent.

The core idea of consentshape is to encode consent decisions into a multidimensional shape. Dimensions may include data categories, processing purposes, geographic or recipient scope, duration, and conditions for withdrawal. In a visualization, the size, volume, or facets of the shape can reflect the breadth of permitted processing, while color or opacity can indicate status or recency. This visual metaphor is intended to complement machine-readable policies by offering an at-a-glance representation that supports user comprehension and operational decision-making.

Implementation concepts involve translating the shape into a machine-readable policy and ensuring interoperability with consent management platforms. A consentshape model might be serialized in JSON-LD or similar formats and mapped to existing data governance rules, revocation mechanisms, and audit trails. It aims to support dynamic updates, versioning, and activity logging so that processors can enforce or adjust processing in response to user actions.

Benefits of consentshape include improved interpretability of consent, potential interoperability across systems, and clearer governance accountability. Challenges involve the lack of formal standardization, potential complexity for users and developers, accessibility considerations, and ensuring consistent interpretation across platforms. It remains primarily a theoretical and experimental concept rather than a standardized framework.