Multiontology

Multiontology is a field within knowledge representation and semantic technologies that focuses on the use, management, and integration of multiple ontologies within a shared framework. It addresses how diverse sources encode knowledge in different vocabularies, structures, and levels of abstraction to enable interoperability across domains, organizations, and applications. Unlike a single monolithic ontology, multiontology accepts that multiple ontologies may coexist and must be related through systematic methods.

Core activities in multiontology include ontology alignment or mapping, where correspondences between concepts, properties, and axioms are established; ontology merging or bridging, which combines compatible parts into a coherent whole; and federated or distributed reasoning, which allows queries and inferences to span multiple ontologies without requiring full consolidation. Modularization is often employed to keep ontologies manageable and reusable. In practice, multionology also uses cross-domain grounding via upper or bridge ontologies and relies on standard vocabularies and metadata to promote interoperability.

Common challenges involve semantic heterogeneity, differing modeling commitments, and expressive differences across ontologies, as well as versioning, provenance, and maintaining alignment over time. Reasoning with multiple ontologies can raise scalability concerns, and conflicts between conflicting axioms or coverage gaps may arise. Evaluation typically requires domain expertise and carefully chosen benchmarks.

Applications of multionology span data integration in enterprises and government, bioinformatics, cultural heritage, and knowledge graphs that combine data from multiple sources. It remains an active area of research, with ongoing work in formal mapping languages, alignment evaluation, and governance frameworks to sustain interoperable, multi-ontology ecosystems.