Ontologies are machine processable artifacts and the core structures of the Semantic Web. OWL (Web Ontology Language) is a W3C Recommendation language for developing ontologies; it is based on Description Logics, allowing for precise knowledge representation and sound and complete automated reasoning over the collection of axioms in an OWL document. Although ontologies are useful for sharing terminologies, their design and reuse are difficult and time consuming processes. Despite the efforts of the community towards the development of OWL ontologies, there is a lack of methods and tools for reusing and inspecting ontologies, i.e., reverse engineering methods. This thesis focuses on the area by investigating the detection of regularities in ontologies, for the purpose of abstracting sets of axioms into patterns that can be verified and reused. Its main contribution is the Regularity Inspector for Ontologies (RIO) framework, which implements methods to find syntactic regularities (repetitive structures in the asserted axioms) and semantic regularities (repetitive structures in the entailments) in an ontology. Regularity detection is achieved through the use of cluster analysis for detecting similarities in sets of axioms. This thesis provides experimental evidence for the effectiveness of regularity analysis for the inspection of patterns, and the discovery of modeling irregularities (often modelling errors) during quality assurance for real, large ontologies. In particular, empirical analysis showed that RIO could successfully detect regularities in ontologies, revealing the patterns adopted by the developers. It can be also used to trace pattern deviations as part of checking conformance to an intended design template during quality assurance of an ontology. This work has been motivated by the existence of pattern based systematic development methodologies and the lack of methods for discovering patterns in existing ontologies --- the natural complement of these pattern based development methodologies.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:574349 |
| Date | January 2013 |
| Creators | Mikroyannidi, Eleni |
| Contributors | Rector, Alan; Stevens, Robert |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://www.research.manchester.ac.uk/portal/en/theses/detection-of-syntactic-andsemantic-regularities-in-ontologies(144ed6a8-51c7-440c-b5ab-32ba9fbfc63f).html |
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