An Ecosystem for Ontology Interoperability
This addresses the challenge of conflicting and overlapping ontologies for developers and users in knowledge graph applications, but it appears incremental as it combines existing techniques.
The paper tackles the problem of ontology interoperability in knowledge graphs by proposing an ecosystem that integrates three semantic techniques across the ontology engineering life cycle, validated through a case study in the building domain.
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 (OE) life cycle: ontology design patterns (ODPs) in the design phase, ontology matching and versioning (OM\&OV) in the develop phase, and data-driven ontology validation (DOVA) in the deploy phase, to achieve better ontology interoperability and data integration in real-world applications. A case study of sensor observation in the building domain validates the usefulness of the proposed ecosystem.