# Axis-Aligned Semantics for ODRL: Resolving Dimensional Ambiguity in Policy Constraints

arXiv: https://arxiv.org/abs/2602.19878 · HTML: https://mlsanity.com/paper/2602.19878/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 29 references that are in the map.
- First posted on arXiv 23 Feb 2026.

## Builds on (most cited first, 3 of 3)

- [Open Digital Rights Enforcement Framework (ODRE): from descriptive to enforceable policies](https://mlsanity.com/paper/2409.17602/) (2024)
- [Evaluation and Comparison Semantics for ODRL](https://mlsanity.com/paper/2509.05139/) (2025)
- [Machine Understandable Policies and GDPR Compliance Checking](https://mlsanity.com/paper/2001.08930/) (2020)

## Abstract (arXiv)

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-specific scalar operands over totally ordered domains. Each constraint then denotes an interval per axis and each policy an axis-aligned box, reducing conflict detection to box comparison. We define a three-valued semantics (Conflict, Compatible, Unknown), prove the decomposition sound and backward compatible with ODRL, instantiate it as ODRL Axis-Aligned Profile (OAAP), and validate it on a benchmark of 256 ODRL policy problems, each expressed in Turtle and compiled to first-order (TPTP) and SMT-LIB form, using Vampire, E, Z3, and cvc5.