Cited By
View all- Kumar SBaliyan NSukalikar S(2017)Ontology Cohesion and Coupling MetricsInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201710010113:4(1-26)Online publication date: 1-Oct-2017
Towards measurement of structural complexity for ontologies
Pages 153 - 173
Abstract
Ontologies represent knowledge of a particular domain and form an elementary unit for inference techniques on the semantic web. It is important to measure the complexity of ontologies in order for users to better understand, maintain, reuse and integrate them. Existing measures for the complexity of an ontology either handle complexity at schema and instance levels or define subjective parameters to measure ontology complexity. To this end, we present a semi-automated framework to measure the structural complexity at different abstraction levels of an ontology. Moreover, our metrics leverage the information provided by ontology editors, which can be useful to the ontology designer for selection of the ontology with optimum complexity among alternative ontologies. Our framework is inspired by the concept of component-based software complexity metrics and its metrics have been validated against Briand's and Weyuker's benchmarks. We have also performed comparative analysis on public ontologies.
References
[1]
Alani, H., Christopher, B. and Nigel, S. (2006) 'Ranking ontologies with AKTiveRank', Fifth International Semantic Web Conference, Springer, Berlin, Heidelberg, pp.1-15.
[2]
Breitman, K., Casanova, M.A. and Truszkowski, W. (2007) Semantic Web: Concepts, Technologies and Applications, Springer Science & Business Media, London.
[3]
Briand, L.C., Sandro, M. and Victor, R.B. (1996) 'Property-based software engineering measurement', IEEE Transactions on Software Engineering, Vol. 22, No. 1, pp.68-86.
[4]
Christopher, A.H. and Nigel, S. (2006) 'Ranking ontologies with AKTiveRank', Fifth International Semantic Web Conference, pp.1-15.
[5]
Ebiquity Group (2007) Swoogle [online] http://swoogle.umbc.edu/ (accessed 14 June 2014).
[6]
Kachroudi, M., Zghal, S. and Ben Yahia, S. (2013) 'OntoPart: at the cross-roads of ontology partitioning and scalable ontology alignment systems', International Journal of Metadata, Semantics and Ontologies, Vol. 8, No. 3, pp.215-225.
[7]
Kang, D., Xu, B., Lu, J. and Chu, W.C. (2004) 'A complexity measure for ontology based on UML', Tenth International Workshop on Future Trends of Distributed Computing Systems, IEEE, pp.222-228.
[8]
Lee, T.B., Hendler, J. and Lassila, O. (2001) 'The semantic web: a new form of web content that is meaningful to computers will unleash a revolution of new possibilities', Scientific American, Vol. 284, No. 5, pp.1-5.
[9]
McCabe, T.J. (1976) 'A complexity measure', IEEE Transactions on Software Engineering, Vol. 2, No. 4, pp.308-320.
[10]
Myers, L. and Sirois, M.J. (2014) Spearman Correlation Coefficients, Differences Between, Wiley StatsRef: Statistics Reference Online, John Wiley & Sons, Inc., NJ, USA.
[11]
Narasimhan, V.L. and Hendradjaya, B. (2007) 'Some theoretical considerations for a suite of metrics for the integration of software components', Information Sciences, Vol. 177, No. 3, pp.844-864.
[12]
Pressman, R.S. (2005) 'Software testing techniques', in Jones, B. (Ed.): Software Engineering: a Practitioner's Approach, pp.474-475, New York, NY.
[13]
Protégé, Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine [online] http://protege.stanford.edu/ (accessed 10 July 2014).
[14]
Sicilia, M.A., Rodríguez, D., Barriocanal, E.G. and Alonso, S.S. (2012) 'Empirical findings on ontology metrics', Expert Systems with Applications, Vol. 39, No. 8, pp.6706-6711.
[15]
Simperl, E.P.B., Tempich, C. and Sure, Y. (2006) 'ONTOCOM: a cost estimation model for ontology engineering', Fifth International Semantic Web Conference, Springer, Berlin, Heidelberg, pp.625-639.
[16]
Tartir, S. and Arpinar, I.B. (2007) 'Ontology evaluation and ranking using OntoQA', IEEE International Conference on Semantic Computing, pp.185-192.
[17]
Tartir, S., Arpinar, I.B., Moore, M., Sheth, A.P. and Meza, B.A. (2005) 'OntoQA: metric-based ontology quality analysis', IEEE Workshop on Knowledge Acquisition from Distributed, Autonomous, Semantically Heterogeneous Data and Knowledge Sources.
[18]
Troullinou, G., Kondylakis, H., Daskalaki, E. and Plexousakis, D. (2015) 'RDF digest: efficient summarization of RDF/S KBs', European Semantic Web Conference, pp.119-134.
[19]
Vrandecic, D. and Sure, Y. (2007) 'How to design better ontology metrics', The Semantic Web: Research and Applications, Springer, Vol. 4519, No. 1, pp.311-325.
[20]
Weinreich, R. and Sametinger, J. (2001) 'Component-based software engineering: putting the pieces together', in Heineman, G.T. and Councill, W.T. (Eds.): p.33-48, Addison-Wesley.
[21]
Weyuker, E.J. (1988) 'Evaluating software complexity measures', IEEE Transactions on Software Engineering, Vol. 14, No. 9, pp.1357-1365.
[22]
Yang, Z., Zhang, D. and Ye, C. (2006) 'Evaluation metrics for ontology complexity and evolution analysis', IEEE International Conference on E-Business Engineering, pp.162-170.
[23]
Zhang, H., Li, Y.F. and Tan, H.B.K. (2010) 'Measuring design complexity of semantic web ontologies', Journal of Systems and Software, Vol. 83, No. 5, pp.803-814.
Recommendations
A combined approach to checking web ontologies
WWW '04: Proceedings of the 13th international conference on World Wide WebThe understanding of Semantic Web documents is built upon ontologies that define concepts and relationships of data. Hence, the correctness of ontologies is vital. Ontology reasoners such as RACER and FaCT have been developed to reason ontologies with a ...
Comparing two ontologies
Ontologies play an important role in applications related to knowledge management, natural language processing, information retrieval, etc. As a result, a large number of ontologies have been developed rapidly. Once an ontology is created, it can be ...
Semantic enrichment for medical ontologies
The Unified Medical Language System (UMLS) contains two separate but interconnected knowledge structures, the Semantic Network (upper level) and the Metathesaurus (lower level). In this paper, we have attempted to work out better how the use of such a ...
Comments
Information & Contributors
Information
Published In
Publisher
Inderscience Publishers
Geneva 15, Switzerland
Publication History
Published: 01 January 2016
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- View Citations1Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 21 Sep 2024
Other Metrics
Citations
Cited By
View all- Kumar SBaliyan NSukalikar S(2017)Ontology Cohesion and Coupling MetricsInternational Journal on Semantic Web & Information Systems10.4018/IJSWIS.201710010113:4(1-26)Online publication date: 1-Oct-2017
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in