Crossontology

Crossontology refers to the practice and study of enabling interoperability among ontologies that describe knowledge in one or more domains. An ontology is a formal representation of concepts and their interrelationships. Crossontology focuses on aligning, mapping, and integrating concepts across ontologies to enable data exchange, querying, and reasoning across systems that use different vocabularies.

Core activities include ontology alignment or mapping, where concepts in one ontology are linked to equivalent or related concepts in another. Strategies include lexical similarity, structural similarity, instance-based reasoning, and background knowledge. Mappings are often expressed using semantic relationships such as equivalentClass, subclassOf, or relatedTo, and exchanged in standards such as the Alignment format or RDF/OWL constructs. Tools and benchmarks, such as the Ontology Alignment Evaluation Initiative, support evaluation of crossontology matching approaches. Upper ontologies and mediating ontologies (e.g., BFO, SUMO) are used to facilitate cross-domain alignment.

Crossontology enables data integration, interoperability of software systems, cross-domain search, and federated queries across heterogeneous databases in fields such as biomedicine, environmental science, and enterprise data management.

Key challenges include semantic heterogeneity, differing granularity and scope, evolving ontologies, mapping ambiguities, and scalability concerns as the number of ontologies grows. Provenance, trust, and maintenance of mappings are also important.

Future directions aim to combine automated matching with human curation, integrate cross-ontology reasoning in knowledge graphs, and leverage machine learning to propose and refine mappings while preserving interpretability. Crossontology remains central to enabling interoperable knowledge ecosystems across diverse domains.