The Efficacy of OWL and DL on User Understanding of Axioms and Their Entailments

Eisa Alharbi, John Howse, Gem Stapleton, Ali Hamie, Anestis Touloumis

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBNpeer-review


OWL is recognized as the de facto standard notation for on- tology engineering. The Manchester OWL Syntax (MOS) was developed as an alternative to symbolic description logic (DL) and it is believed to be more eective for users. This paper sets out to test that belief from two perspectives by evaluating how accurately and quickly people understand the informational content of axioms and derive inferences from them. By conducting a between-group empirical study, involving 60 novice participants, we found that DL is just as eective as MOS for people's understanding of axioms. Moreover, for two types of inference problems, DL supported signi cantly better task performance than MOS, yet MOS never signi cantly outperformed DL. These surprising results suggest that the belief that MOS is more eective than DL, at least for these types of task, is unfounded. An outcome of this research is the suggestion that ontology axioms, when presented to non experts, may be better presented in DL rather than MOS. Further empirical studies are needed to explain these unexpected results and to see whether they hold for other types of task.
Original languageEnglish
Title of host publicationISWC2017 The 16th International Semantic Web Conference
Place of PublicationVienna
Number of pages17
ISBN (Print)9783319682877
Publication statusPublished - 4 Oct 2017
EventISWC2017 The 16th International Semantic Web Conference - Vienna, Austria, 21-25 October 2017
Duration: 4 Oct 2017 → …

Publication series

NameLecture Notes in Computer Science


ConferenceISWC2017 The 16th International Semantic Web Conference
Period4/10/17 → …

Bibliographical note

The final publication is available at Springer via


  • ontologies
  • OWL
  • DL
  • Manchester OWL Syntax
  • usability


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