Abstract
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 language | English |
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Title of host publication | ISWC2017 The 16th International Semantic Web Conference |
Place of Publication | Vienna |
Publisher | Springer |
Pages | 20-36 |
Number of pages | 17 |
ISBN (Print) | 9783319682877 |
Publication status | Published - 4 Oct 2017 |
Event | ISWC2017 The 16th International Semantic Web Conference - Vienna, Austria, 21-25 October 2017 Duration: 4 Oct 2017 → … |
Publication series
Name | Lecture Notes in Computer Science |
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Conference
Conference | ISWC2017 The 16th International Semantic Web Conference |
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Period | 4/10/17 → … |
Bibliographical note
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-68288-4_2Keywords
- ontologies
- OWL
- DL
- Manchester OWL Syntax
- usability
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Anestis Touloumis
- School of Arch, Tech and Eng - Principal Lecturer
- Computing and Mathematical Sciences Research Excellence Group
Person: Academic