Ontologies over the Semantic Web

Krzysztof Goczyła, Teresa Zawadzka


One of the major and most challenging tasks for modern Information Technology is development of methods aimed at automatically acquiring and processing knowledge stored in the biggest information repository the man has ever created – the Internet. This knowledge is of miscellaneous nature, mainly due to the fact that it is stored in many languages and in numerous formats with different levels of structur­ing. The “Semantic Web initiative” strives to achieve this goal by struc­turing the con­tents of Internet into publicly available and shared ontologies formulated in a com­monly accepted, machine readable format. In this paper we discuss problems of build­ing ontologies and using them throughout Semantic Web. Relevant topics are pre­sented in the broader context of knowledge representation methods. We also present an alternative approach based on processing textual Web contents, extracting seman­tics from them and creating a “general ontology” to be used to present knowledge to a user.


knowledge representation; ontologies; frames; description logics; Semantic Web

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ARPA/Rome Laboratory Planning Initiative http://aaaipress.org/Library/ARPI/arpi96-contents.php

Baader F. A., McGuiness D. L., Nardi D., Patel-Schneider P. F.: The Description Logic Handbook: Theory, implementation, and applications. Cambridge University Press, 2003.

Bechhofer S.: The DIG Description Logic Interface: DIG/1.1. University of Manchester, 2003.

Berners-Lee T., Hendler J., Lassila O.: .The Semantic Web. Scientific American, May 2001.

Borst P.: Construction of Engineering Ontologies for Knowledge Sharing and Reuse. PhD thesis, Tweente University, 1997.

Dym C. L., Levitt R. E.: Knowledge-based Systems in Engineering. McGraw-Hill, Inc., 1991.

Evaluation and Language resources Distribution Agency http://www.elda.fr.

GALEN http://www.openclinical.org/prj_galen.html.

Goczyła K., Grabowska T., Waloszek W., Zawadzki M.: The Cartographer Algorithm for Processing and Querying Description Logics Ontologies. Lectuire Notes in Computer Science, Vol. 3528 (2005), Ed. Springer Verlag, s. 163-169.

Gruber T., Olsen G. R.: An Ontology for Engineering Mathematics. W: E. S. J. Doyle & P. Torasso, eds, 'KR94 Proceedings', Morgan Kaufmann, s. 258-269, 1994.

Haarslev V., Molier R.: RACER User's Guide and Reference Manual. September 17, 2003, http://www.cs.concordia.ca/~haarslev/racer/racer-manual-l-7-7.pdf.

Horrocks, I. FaCT Reference Manual vi.6, August 1998, FaCT archive: http://www.cs-.man.ac .uk/~horrocks/FaCT.

KACTUS ontology library. http://hcs.science.uva.nl/projects/Kactus/toolkit/intro.html.

Linguistic Data Consortium www.ldc.upenn.edu.

Minsky M.: A Framework for Representing Knowledge. W: The Psychology of Computer Vision. Ed. P.H.Winston, McGraw-Hill, New York, 1975, s. 21K277.

OWL Web Ontology Language Reference. www.w3.org/TR/owl-ref.

Pinto S., Gomez-Perez, Martins L: Some Issues on Ontology Integration. W: Proceedings of the JCAI-99 Workshop on Ontologies and Problem-Solving Methods (KRR5), Stockholm, Sweden, 1999.

The Rule Markup Initiative RuleML http://www.ruleml.org/.

Russel S. J., Norvig, P.: Artificial Intelligence. A modern Approach. Second Edition. Pearson Education International. 2003.

A Semantic Web Framework for Java, http://jena.sourceforge.net/.

Staab S., Studer R. (eds): Handbook on Ontologies. Springer Verlag, 2004.

W3C Semantic Web Activity, www.w3.org/2001/sw.

UMLS http://www.nlm.nih.gov/research/umls/.

Winston M., Chaffin R., Herrmann D.: A taxonomy of part-whole relationships. W: Cognitive Science, rozdz. 11, s. 417^444, 1987.

WordNet http://wordnet.princeton.edu/.

RDF Primer http://www.w3.org/TR/rdf-primer/.

DOI: http://dx.doi.org/10.21936/si2006_v27.n2.572