Publication | Open Access
Schema and ontology matching with COMA++
633
Citations
8
References
2005
Year
Unknown Venue
Ontology MatchingEngineeringOntology EngineeringSemanticsSemantic WebOntology-based Data IntegrationInformation RetrievalData ScienceOntology MergingManagementData IntegrationOntology AlignmentSchema MatchingData ManagementComputer SciencePrevious Prototype ComaTool Coma++Data ModelingSemantic Interoperability
COMA++ extends the earlier COMA prototype by combining multiple match algorithms into a composite approach. The paper demonstrates the schema and ontology matching tool COMA++. COMA++ offers a graphical interface, a generic data representation that supports schemas and ontologies such as W3C XML Schema and OWL, and incorporates new ontology‑matching approaches—including shared taxonomies, reusable match results, and fragment‑based decomposition—to enable varied match strategies and comparative evaluation of algorithms. COMA++ delivers significant improvements and a comprehensive infrastructure capable of solving large real‑world schema and ontology matching problems.
We demonstrate the schema and ontology matching tool COMA++. It extends our previous prototype COMA utilizing a composite approach to combine different match algorithms [3]. COMA++ implements significant improvements and offers a comprehensive infrastructure to solve large real-world match problems. It comes with a graphical interface enabling a variety of user interactions. Using a generic data representation, COMA++ uniformly supports schemas and ontologies, e.g. the powerful standard languages W3C XML Schema and OWL. COMA++ includes new approaches for ontology matching, in particular the utilization of shared taxonomies. Furthermore, different match strategies can be applied including various forms of reusing previously determined match results and a so-called fragment-based match approach which decomposes a large match problem into smaller problems. Finally, COMA++ cannot only be used to solve match problems but also to comparatively evaluate the effectiveness of different match algorithms and strategies.
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