Updating OWL2 ontologies using pruned rulesets
Al Azwari, Sana and Wilson, John N. (2015) Updating OWL2 ontologies using pruned rulesets. In: 11th International Conference on Semantic Systems, 2015-09-16 - 2015-09-17, Vienna University of Economics. (https://doi.org/10.1145/2814864.2814871)
Preview |
Text.
Filename: Al_Azwari_Wilson_ICSS_2015_Updating_OWL2_ontologies_using_pruned.pdf
Accepted Author Manuscript Download (1MB)| Preview |
Abstract
Evolution in Semantic Web content produces difference files (deltas) that track changes between RDF versions. These changes may represent ontology modifications and be expressed in OWL. The deltas can be used to reduce the storage and bandwidth overhead involved in disseminating ontology updates. Minimising the delta size can be achieved by reasoning over the underlying knowledge base. OWL 2 is a development of the OWL 1 standard that incorporates new features to aid application development. Among the sub languages of OWL 2, OWL 2 RL/RDF provides an enriched rule set that extends the semantic capability of the OWL environment. This additional semantic content can be exploited in change detection approaches that strive to minimise the alterations to be made when ontologies are updated. The presence of blank nodes (i.e. nodes that are neither a URI nor a literal) in RDF collections provides a further challenge to ontology change detection because of the practical problems they introduce when comparing data structures before and after update. In the light of OWL 2 RL/RDF, this paper examines the potential for reducing the delta size by pruning the application of unnecessary rules from the reasoning process and using an approach to delta generation that produces the smallest number of updates. It also assesses the impact of alternative approaches to handling blank nodes during the change detection process in ontology structures. The results indicate that pruning the rule set is a potentially expensive process but has the benefit of reducing the joins when carrying out the subsequent inferencing.
ORCID iDs
Al Azwari, Sana ORCID: https://orcid.org/0000-0002-6659-541X and Wilson, John N. ORCID: https://orcid.org/0000-0002-5297-657X;-
-
Item type: Conference or Workshop Item(Paper) ID code: 58739 Dates: DateEvent15 September 2015Published24 July 2015AcceptedNotes: Winner of the Best Paper award at the 11th International Conference on Semantic Systems, Vienna, Sept 2015. Subjects: Science > Mathematics > Computer software Department: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 17 Nov 2016 15:42 Last modified: 27 Nov 2024 01:38 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/58739