LogMap family results for OAEI 2015.

We present the results obtained in the OAEI 2015 campaign by our ontology matching system LogMap and its variants: LogMapC, LogMapBio and LogMapLt. The LogMap project started in January 2011 with the objective of de- veloping a scalable and logic-based ontology matching system. This is our sixth participation in the OAEI and the experience has so far been very positive. Cur- rently, LogMap is the only system that participates in all OAEI tasks. 1 Presentation of the system Ontology matching systems typically rely on lexical and structural heuristics and the integration of the input ontologies and the mappings may lead to many undesired log- ical consequences. In (12) three principles were proposed to minimize the number of potentially unintended consequences, namely: (i) consistency principle, the mappings should not lead to unsatisfiable classes in the integrated ontology; (ii) locality principle, the mappings should link entities that have similar neighbourhoods; (iii) conservativ- ity principle, the mappings should not introduce alterations in the classification of the input ontologies. Violations to these principles may hinder the usefulness of ontology mappings. The practical effect of these violations, however, is clearly evident when ontology alignments are involved in complex tasks such as query answering (19). LogMap (11, 13) is a highly scalable ontology matching system that implements the consistency and locality principles. LogMap also supports (real-time) user interaction during the matching process, which is essential for use cases requiring very accurate mappings. LogMap is one of the few ontology matching system that (i) can efficiently match semantically rich ontologies containing tens (and even hundreds) of thousands of classes, (ii) incorporates sophisticatedhttp://iswc2015.semanticweb.org/ reasoning and repair techniques to minimise the number of logical inconsistencies, and (iii) provides support for user intervention during the matching process.