Abstract
The ODRL policy language is emerging as the de-facto standard for policy modeling data access and usage preferences, AI governance policies, and data workflows in European dataspaces. The current standard lacks a mathematical formal semantics to describe how a system should implement policy evaluation, leading to various systems and tools that implement their own interpretations of the language, limiting interoperability and failing to guarantee consistent results.
Based on an existing semantic model of ODRL, we formalize the problems of ODRL evaluation for access control and monitoring scenarios in both static and streaming settings and provide a novel, efficient algorithm and implementation. We present the first ODRL Evaluator with transparent formal semantics supporting all rule types.
We experimentally measure its performance, analyzing different scalability dimensions related to policy complexity and data size on which a policy is evaluated. We compare our system with state-of-the-art by providing a comparative review of existing ODRL evaluators, highlighting the differences in supported ODRL features and evaluation modes.
Blogger's Review: This paper provides a systematic solution for ODRL evaluation, particularly valuable in the absence of a unified standard. The introduction of a transparent semantic implementation is significant, and the performance benchmarks offer a reference point for future research.