OntoLDiff: A Highly Efficient System for Tracking Logical Difference in Large-Scale Ontologies

Modern ontologies undergo continuous evolution to accommodate new domain knowledge, correct modeling errors, and adapt to changing user requirements. Monitoring these changes is crucial for maintaining ontology quality and understanding the semantic impact of modifications on dependent systems and applications. This paper describes OntoLDiff, a highly efficient system for tracking the logical difference between two ontologies formulated in the description logic ELH. Intuitively, the logical difference between two versions of an ontology refers to the set of axioms entailed by one version but not the other, indicating the information gain or loss between them. Typically, such axioms, referred to as 'witnesses ', can be infinite, making logical difference computation infeasible. To address this challenge, OntoLDiff employs a Uniform Interpolation (UI) approach to compute a finite representation of these axioms. Instead of computing all the entailments of one ontology but not the other, which would be computationally infeasible, the UI-based approach focuses on identifying only the strongest entailments, from which all witnesses can in principle be computed from its deductive closure. Despite UI's computational complexity, OntoLDiff is currently the only tool that efficiently tracks logical differences in industrial-scale ontologies, enabling ontology curators to precisely identify meaningful changes during ontology evolution.