Investigation Phase: Quantitative Analysis of Domain Ontology Usage (QUA-AF)

Ashraf, J; Hussain, OK; Hussain, FK; Chang, EJ

Investigation Phase: Quantitative Analysis of Domain Ontology Usage (QUA-AF)

Ashraf, J Hussain, OK Hussain, FK

Chang, EJ

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Publication Type:: Chapter
Citation:: Studies in Computational Intelligence, 2018, 767 pp. 141 - 169
Issue Date:: 2018-01-01

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Field	Value	Language
dc.contributor.author	Ashraf, J	en_US
dc.contributor.author	Hussain, OK	en_US
dc.contributor.author	Hussain, FK https://orcid.org/0000-0003-1513-8072	en_US
dc.contributor.author	Chang, EJ	en_US
dc.date.issued	2018-01-01	en_US
dc.identifier.citation	Studies in Computational Intelligence, 2018, 767 pp. 141 - 169	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133068
dc.description.abstract	© 2018, Springer International Publishing AG, part of Springer Nature. In the previous chapter, the EMP-AF was proposed to perform an empirical analysis of domain ontology usage. The empirical analysis, through its observed factors such as the relationship between different ontologies based on an entity’s semantic description, ontology component usage, contextual description, and provision and availability of knowledge patterns, helps us to understand the uptake and adoption of domain ontologies on the Web. In other words, it gives a comprehensive analysis of the “usage” aspect of a domain ontology and its components. While the insights obtained through EMP-AF highlight the key aspects of the usage dimension, two other dimensions warrant consideration to fully realize the perceived benefits of Ontology Usage Analysis (OUA), as mentioned in Chap. 3, and to enable the quantitative analysis of OUA. These are the “technology” and “business” dimensions, which also have a direct relationship with ontology adoption and usage.	en_US
dc.relation.ispartof	Studies in Computational Intelligence	en_US
dc.relation.isbasedon	10.1007/978-3-319-75681-3_6	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Investigation Phase: Quantitative Analysis of Domain Ontology Usage (QUA-AF)	en_US
dc.type	Chapter
utslib.citation.volume	767	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Software
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.declined	2019-05-03T16:54:43.267+1000
pubs.publication-status	Published	en_US
pubs.volume	767	en_US

Abstract:

© 2018, Springer International Publishing AG, part of Springer Nature. In the previous chapter, the EMP-AF was proposed to perform an empirical analysis of domain ontology usage. The empirical analysis, through its observed factors such as the relationship between different ontologies based on an entity’s semantic description, ontology component usage, contextual description, and provision and availability of knowledge patterns, helps us to understand the uptake and adoption of domain ontologies on the Web. In other words, it gives a comprehensive analysis of the “usage” aspect of a domain ontology and its components. While the insights obtained through EMP-AF highlight the key aspects of the usage dimension, two other dimensions warrant consideration to fully realize the perceived benefits of Ontology Usage Analysis (OUA), as mentioned in Chap. 3, and to enable the quantitative analysis of OUA. These are the “technology” and “business” dimensions, which also have a direct relationship with ontology adoption and usage.

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http://hdl.handle.net/10453/133068