arXiv:2602.19878v3 Announce Type: replace Abstract: The Open Digital Rights Language (ODRL) represents policy constraints as triples of a left operand, an operator, and a value. Several spatial operands, however, range over multi-axis domains such as width, height, and depth, while the constraint syntax provides no explicit axis identity. As a result, policy engines cannot determine whether multiple constraints apply to the same axis or different ones, making conflict detection unsound or incomplete. We resolve this ambiguity by axis decomposition, replacing multi-axis operands with axis-speci
The increasing complexity of digital rights management and policy enforcement, particularly in multi-dimensional data spaces, necessitates clearer semantic definitions for robust AI systems.
This development improves the reliability and soundness of policy enforcement in distributed digital environments, crucial for AI systems that operate under complex legal and contractual frameworks.
Policy engines can now definitively resolve ambiguity in multi-axis spatial constraints, leading to more accurate conflict detection and policy application.
- · Developers of digital rights management (DRM) systems
- · Organizations enforcing complex data usage policies
- · AI systems requiring precise policy interpretation
- · Systems reliant on ambiguous policy definitions
Reduced errors and conflicts in digital rights enforcement through explicit axis identity.
Improved interoperability and trust in data sharing agreements where digital rights are critical.
Acceleration of secure, policy-driven data marketplaces and decentralized autonomous organizations (DAOs) using ODRL.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.CL