🤖 AI Summary
Ontology evolution in the Semantic Web is accelerating, yet traditional ontology versioning (OV) approaches suffer from low accuracy and poor scalability due to exponential growth in ontology size and heavy reliance on manual intervention.
Method: This paper proposes a novel OV paradigm grounded in ontology matching (OM), establishing a unified OM4OV pipeline. It systematically adapts OM techniques to OV tasks, reformulates the OV problem definition, evaluation metrics, and benchmarks—extending the OAEI dataset—and introduces cross-reference (CR) mechanisms and alignment reuse strategies to enhance robustness in identifying version differences.
Contribution/Results: Experiments demonstrate significant improvements in concept mapping accuracy. Notably, several mappings previously misclassified as erroneous are revealed to reflect legitimate evolutionary relationships, thereby reducing manual verification effort and improving versioning reliability.
📝 Abstract
Due to the dynamic nature of the semantic web, ontology version control is required to capture time-varying information, most importantly for widely-used ontologies. Despite the long-standing recognition of ontology versioning (OV) as a crucial component for efficient ontology management, the growing size of ontologies and accumulating errors caused by manual labour overwhelm current OV approaches. In this paper, we propose yet another approach to performing OV using existing ontology matching (OM) techniques and systems. We introduce a unified OM4OV pipeline. From an OM perspective, we reconstruct a new task formulation, measurement, and testbed for OV tasks. Reusing the prior alignment(s) from OM, we propose a pipeline optimisation method called cross-reference (CR) mechanism to improve overall OV performance. We experimentally validate the OM4OV pipeline and the cross-reference mechanism in modified Ontology Alignment Evaluation Initiative (OAEI) datasets. We also discuss the insights on OM used for OV tasks, where some false mappings detected by OV systems are not actually false.