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Differentiating conceptual modelling from data modelling, knowledge modelling and ontology modelling and a notation for ontology modelling

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Conferences in Research and Practice in Information Technology Series; Vol. 325 archive
Proceedings of the fifth on Asia-Pacific conference on conceptual modelling - Volume 79 table of contents

Wollongong, NSW, Australia

SESSION: Invited papers table of contents

Pages: 7-17

Year of Publication: 2008

ISBN ~ ISSN:1445-1336 , 978-1-920682-60-6

Authors

Tharam Dillon | Curtin University of Technology, Perth, Western Australia
Elizabeth Chang | Curtin University of Technology, Perth, Western Australia
Maja Hadzic | Curtin University of Technology, Perth, Western Australia
Pornpit Wongthongtham | Curtin University of Technology, Perth, Western Australia

Sponsors

: University of Wollongong, Australia
Australian Comp Soc : Australian Computer Society
: The University of Waikato
CORE : Computing Research and Education
: Massey University

Publisher

Australian Computer Society, Inc.  Darlinghurst, Australia, Australia

Bibliometrics

Downloads (6 Weeks): 8,   Downloads (12 Months): 83,   Citation Count: 2

Additional Information:

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ABSTRACT

This paper considers conceptual modelling for three purposes namely data modelling, knowledge modelling and ontology modelling. It differentiates between the nature of the conceptual models for these three. It then proposes a representation suitable for ontology modelling.

REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

1

Dillon, TS, Chang, E & W., R 2008, Object Oriented and Component based Conceptual Modeling and Design.

2

Tharam S. Dillon , Poh L. Tan, Object-Oriented Conceptual Modeling, Prentice Hall PTR, Upper Saddle River, NJ, 1993

3

Farquhar, A., Fikes, R. and Rice, J. (1996): 'The Ontolingua Server: A Tool for Collaborative Ontology Construction', 10th Knowledge Acquisition for Knowledge-Based Systems Workshop, Banff, Canada.

4

Genesereth, M. R. and Fikes, R. E. (1992): Knowledge Interchange Format Version 3 Reference Manual, Stanford University Logic Group.

5

Russell Greiner , Christian Darken , N. Iwan Santoso, Efficient reasoning, ACM Computing Surveys (CSUR), v.33 n.1, p.1-30, March 2001  [doi>10.1145/375360.375363]

6

Thomas R. Gruber, A translation approach to portable ontology specifications, Knowledge Acquisition, v.5 n.2, p.199-220, June 1993  [doi>10.1006/knac.1993.1008]

7

Kuhn, O. and Abecker, A. (1997): Corporate Memories for Knowledge Management in Industrial Practice: Prospects and Challenges. Journal of Universal Computer Science 3(8):929--954.

8

Robert M. MacGregor, Inside the LOOM description classifier, ACM SIGART Bulletin, v.2 n.3, p.88-92, June 1991  [doi>10.1145/122296.122309]

9

Alexander D. Maedche, Ontology Learning for the Semantic Web, Kluwer Academic Publishers, Norwell, MA, 2002

10

Peter Spyns , Robert Meersman , Mustafa Jarrar, Data modelling versus ontology engineering, ACM SIGMOD Record, v.31 n.4, December 2002  [doi>10.1145/637411.637413]

CITED BY  2

Philip H. P. Nguye , Ken Kaneiwa , Dan R. Corbett , Minh-Quang Nguyen, Meta-relation and ontology closure in conceptual structure theory, Artificial Intelligence and Law, v.17 n.4, p.291-320, December 2009

Maja Hadzic , Elizabeth Chang, Application of digital ecosystem design methodology within the health domain, IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, v.40 n.4, p.779-788, July 2010

INDEX TERMS

Keywords:
conceptual modelling, data modelling, knowledge modelling, ontology modelling

Collaborative Colleagues:

Tharam Dillon: colleagues

Elizabeth Chang: colleagues

Maja Hadzic: colleagues

Pornpit Wongthongtham: colleagues

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