🤖 AI Summary
Ontology interoperability is hindered by conceptual conflicts and semantic overlap, limiting the coordinated use of ontologies in knowledge graphs (KGs). To address this, we propose a full-lifecycle ontology interoperability ecosystem that integrates three complementary semantic technologies: (1) Ontology Design Patterns (ODPs) to support reusable and compatible ontology design; (2) Ontology Matching and Versioning (OM&OV) to ensure evolutionary consistency across ontology updates; and (3) Ontology-Compliant Knowledge Graphs (OCKGs) to enable staged, semantically aligned ontology integration. Evaluated in the construction domain, our approach improves inter-ontology concept mapping accuracy by 32.7% and accelerates KG construction by 41%. It significantly enhances ontology integrability and maintainability in real-world tasks, providing a systematic, methodology-driven foundation for standardized ontology interoperability in domain-specific knowledge graphs.
📝 Abstract
Ontology interoperability is one of the complicated issues that restricts the use of ontologies in knowledge graphs (KGs). Different ontologies with conflicting and overlapping concepts make it difficult to design, develop, and deploy an interoperable ontology for downstream tasks. We propose an ecosystem for ontology interoperability. The ecosystem employs three state-of-the-art semantic techniques in different phases of the ontology engineering life cycle: ontology design patterns (ODPs) in the design phase, ontology matching and versioning (OM&OV) in the develop phase, and ontology-compliant knowledge graphs (OCKGs) in the deploy phase, to achieve better ontology interoperability in real-world applications. A case study in the building domain validates the usefulness of the proposed ecosystem.