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{{Publikation Details
|Abstract=Constructing ontologies for real-world knowledge-intensive
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|Abstract=Constructing ontologies for real-world knowledge-intensive applications is a time-consuming and difficult task. As the amount of available OWL ontologies and their size grow, ontology reuse gains in importance. However, differences in requirements lead to conceptual and logical heterogeneity of semantic resources that model related domains. In this paper, we propose methods to support the verification of conceptual and logical suitability of OWL ontologies. We show that our methods significantly reduce the manual effort measured in number of decisions that have to be made by an ontology engineer.
  applications is a time-consuming and difficult task. As the amount
 
  of available OWL ontologies and their size grow, ontology reuse
 
  gains in importance. However, differences in requirements lead to
 
  conceptual and logical heterogeneity of semantic resources that model
 
  related domains. In this paper, we propose methods to support the
 
  verification of conceptual and logical suitability of OWL
 
  ontologies. We show that our methods significantly reduce the manual
 
  effort measured in number of decisions that have to be made by an
 
  ontology engineer.
 
 
|Projekt=NanOn
 
|Projekt=NanOn
 
|Forschungsgruppe=Wissensmanagement
 
|Forschungsgruppe=Wissensmanagement
 
}}
 
}}

Version vom 9. Mai 2010, 17:56 Uhr

Semi-Automatic Verification of Ontology Compatibility Supported by Reasoning




Published: 2010 Februar
Type: Research Notes
Institution: Institut AIFB, KIT
Erscheinungsort / Ort: Karlsruhe
Archivierungsnummer:3004

BibTeX



Kurzfassung
Constructing ontologies for real-world knowledge-intensive applications is a time-consuming and difficult task. As the amount of available OWL ontologies and their size grow, ontology reuse gains in importance. However, differences in requirements lead to conceptual and logical heterogeneity of semantic resources that model related domains. In this paper, we propose methods to support the verification of conceptual and logical suitability of OWL ontologies. We show that our methods significantly reduce the manual effort measured in number of decisions that have to be made by an ontology engineer.


Projekt

NanOn



Forschungsgruppe

Wissensmanagement


Forschungsgebiet