Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-19T17:46:39.305Z Has data issue: false hasContentIssue false
  • English
  • Français

A dynamic knowledge modeler

Published online by Cambridge University Press:  16 December 2008

Robert Harrison  and
Christine W. Chan
Robert Harrison
Affiliation:
Energy Informatics Laboratory, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada
Christine W. Chan
Affiliation:
Energy Informatics Laboratory, Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper presents the development and application of a software tool for modeling knowledge to be used in knowledge-based systems or the Semantic Web. The inferential modeling technique, which is a technique for modeling the static and dynamic knowledge elements of a problem domain, provided the basis for the tool. A survey of existing knowledge modeling tools revealed they typically failed to provide support in four main areas: support for an ontological engineering methodology or technique, support for dynamic knowledge modeling, support for dynamic knowledge testing, and support for ontology management. Dyna, a Protégé plug-in, has been developed, which supports the Inferential Modeling Technique, dynamic knowledge modeling, and dynamic knowledge testing. Protégé and Dyna are applied for constructing an ontological model in the domain of selecting a remediation technology for petroleum contaminated sites. Dynamic knowledge testing in Dyna enabled creation of a more complete knowledge model.

Keywords

Knowledge EngineeringOntologySemantic WebSoftware Engineering
Type
Research Article
Information
AI EDAM , Volume 23 , Issue 1: Developing and Using Engineering Ontologies , February 2009 , pp. 53 - 69
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The Semantic Web. Scientific American 2001 (May), 35–43.Google ScholarPubMed
Chan, C.W. (2004). From knowledge modeling to ontology construction. International Journal of Software Engineering and Knowledge Engineering 14(6).CrossRefGoogle Scholar
Chan, C.W., Huang, G., & Hu, Z. (2002). Development of an Expert Decision Support System for Selection of Remediation Technologies for Petroleum-Contaminated Sites. Rep. No. 00-03-018. Regina, Canada: University of Regina, Petroleum Technology Research Center.Google Scholar
Chen, L. (2001). Construction of an ontology for the domain of selecting remediation techniques for petroleum contaminated sites. MSc Thesis. University of Regina, Canada.Google Scholar
Cranefield, S., Pan, J., & Purvis, M. (2000). A UML ontology and derived content language for a travel booking scenario. In Ontologies for Agents: Theory and Experiences (Tamma, V. et al. , Eds.), pp. 259–276. Basel: Birkhäuser Verlag.Google Scholar
Fensel, D., Harmelen, F. van, Ding, Y., Klein, M., Akkermans, H., Broekstra, J., Kampman, A., van der Meer, J.Studer, R., Sure, Y., Davies, J., Duke, A., Engels, R., Iosif, V., Kiryakov, A., Lau, T., Reimer, U., & Horrocks, I. (2002). On-to-knowledge in a nutshell. IEEE Computer.Google Scholar
Gabel, T., Sure, Y., & Voelker, J. (2004, April 7). KAON—An Overview. Technical Report, University of Karlsruhe, Insitute AIFB.Google Scholar
Gal, A., Eyal, A., Roitman, H., Jamil, H., Anaby-Tavor, A., Modica, G., & Enan, M. (2006). OntoBuilder. Accessed at http://iew3.technion.ac.il/OntoBuilder/Google Scholar
Gasevic, D., Djuric, D., & Devedzic, V. (2005). Ontology modeling and MDA. Journal of Object Technology 4(1), 109–128.Google Scholar
Gennari, J.H., Musen, M.A., Fergerson, R.W., Grosso, W.E., Crubezy, M., Eriksson, H., Noy, N.F., & Tu, S.W. (2003). The evolution of Protégé: an environment for knowledge-based systems development. International Journal of Human–Computer Studies 58(1), 89–123.CrossRefGoogle Scholar
Gomez-Perez, A., Fernandez-Lopez, M., & Corcho, O. (2003). WebODE ontology engineering platform. Accessed at http://webode.dia.fi.upm.es/WebODEWeb/index.htmlGoogle Scholar
Gomez-Perez, A., Fernandez-Lopez, M., & Corcho, O. (2005). Ontological Engineering: With Examples From the Areas of Knowledge Management, e-Commerce, and the Semantic Web. Berlin: Springer.Google Scholar
Gruber, T. (1993). Towards principles for the design of ontologies used for knowledge sharing. In Formal Ontology in Conceptual Analysis and Knowledge Representation (Guarino, N., & Poli, R., Eds.). Padua, Italy: Kluwer.Google Scholar
Guarino, N. (1998). Formal ontology in information systems. Proc. 1st Int. Conf. Formal Ontology in Information Systems (FOIS′98), pp. 3–15. Amsterdam: IOS Press.Google Scholar
Harrison, R., & Chan, C.W. (2005). Implementation of an application ontology: a comparison of two tools. Artificial Intelligence Applications and Innovations II:2nd IFIP TC12 and WG12 Conf. Artificial Intelligence Applications and Innovations (AIAI-2005), pp. 131–143, Beijing, September 7–9.CrossRefGoogle Scholar
Harrison, R., & Chan, C.W. (2007). Tools for industrial knowledge modeling. Proc. 20th Annual Canadian Conf. Electrical and Computer Engineering (CCECE′07)Vancouver, April 22–26.Google Scholar
Horridge, M. (2005 a). OWL unit test framework. Accessed at http://www.co-ode.org/downloads/owlunittest/Google Scholar
Horridge, M. (2005 b). Protégé OWLViz. Accessed at http://www.co-ode.org/downloads/owlviz/co-ode-index.phpGoogle Scholar
Janzen, D., & Saiedian, H. (2005). Test driven development: concepts, taxonomy, and future direction. IEEE Computer 38(9), 43–50.CrossRefGoogle Scholar
McGuiness, D., Fikes, R., Rice, J., & Wilder, S. (2000). An environment for merging and testing large ontologies. Proc. KR 2000, pp. 485–493.Google Scholar
McGuiness, D., Fikes, R., & Feigenbaum, E. (2003). Ontolingua. Accessed at http://www.ksl.stanford.edu/software/ontolingua/Google Scholar
Obst, D. (2006). Distributed framework for knowledge evolution. University of Regina Graduate Student Conf., Regina, SK, Canada.Google Scholar