Analysing Ontological Structures through Name Pattern Tracking

Authors:
Ondřej Šváb-Zamazal;Vojtěch Svátek
Affiliations:
Dept. Information and Knowledge Engineering, University of Economics, Prague, Prague, Czech Republic;Dept. Information and Knowledge Engineering, University of Economics, Prague, Prague, Czech Republic
Venue:
EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
Year:
2008

Citing 6
Cited 2

GenTax: A Generic Methodology for Deriving OWL and RDF-S Ontologies from Hierarchical Classifications, Thesauri, and Inconsistent Taxonomies

ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
How to Design Better Ontology Metrics

ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Learning Disjointness for Debugging Mappings between Lightweight Ontologies

EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
Matching hierarchical classifications with attributes

ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Reconciling concepts and relations in heterogeneous ontologies

ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
Encoding classifications into lightweight ontologies

ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications

OntoCase-Automatic Ontology Enrichment Based on Ontology Design Patterns

ISWC '09 Proceedings of the 8th International Semantic Web Conference
Inspecting regularities in ontology design using clustering

ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

Concept naming over the taxonomic structure is a useful indicator of the quality of design as well as source of information exploitable for various tasks such as ontology refactoring and mapping. We analysed collections of OWL ontologies with the aim of determining the frequency of several combined name&graph patterns potentially indicating underlying semantic structures. Such structures range from simple set-theoretic subsumption to more complex constructions such as parallel taxonomies of different entity types. The final goal is to help refactor legacy ontologies as well as to ease automatic alignment among different models. The results show that in most ontologies there is a significant number of occurrences of such patterns. Moreover, their detection even using very simple methods has precision sufficient for a semi-automated analysis scenario.