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The Spiral_OWL Model – Towards Spiral Knowledge Engineering

Authors: Hafizullah A. Hashim, Aniza. A

Abstract:

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

Keywords: Domain Expert, Knowledge Base, Ontology, Software Process.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1334237

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References:


[1] A. Gomez-Perez, M. Fernandez-Lopez, and M. De Vicente, Towards a Method to Conceptualize Domain Ontologies. In working notes of the workshop on Ontological Engineering, ECAI-96, pp. 41-52, ECCAI 1996.
[2] A. R. Puerta, J.W. Egar, S. W. Tu, M. A. Musen, A Multiple-Method Knowledge Acquisition Shell for the Automatic Generation of Knowledge Acquisition Tools, Knowledge Acquisition 4 (1992), pp. 171-196
[3] A. T. Schreiber, B. J. Wielinga, R. de Hoog, H. Akkermans, W. Van de Velde, CommonKads: A Comprehensive Methodology for KBS Development, IEEE Expert (December 1994), pp. 28-37
[4] B. Boehm, A Spiral Model of Software Development and Enhancement, Computer, May 1988, pp. 61-72
[5] G. Schreiber, H. Akkermans, A. Anjewierden, R. de Hoog, N. Shadbolt, W. V. de Velde, and B. J. Wielinga, Knowledge Engineering and Management: The CommonKADS Methodology, MITpress, 2000
[6] H. Knublauch, An Agile Development Methodology for Knowledge- Based Systems, PhD thesis, University of Ulm, 2002
[7] J. Angele, D. Fensel, R. Studer, Developing Knowledge-Based Systems with MIKE, Journal of Automated Software Engineering, in press
[8] J. M. David, J. P. Krivine, R. Simmons (eds.), Second Generation Expert Systems (Springer-Verlag, Berlin, 1993)
[9] K. Morik, Underlying Assumptions of Knowledge Acquisition as a Process of Model Refinement, Knowledge Acquisition 2(1), March 1990, pp. 21-49.
[10] M. A. Musen, An Overview of Knowledge Acquisition, in J.M. David et al. (eds.), Second Generation Expert Systems (Springer-Verlag, 1993)
[11] Paulk M. C., Curtis, B., Chrissis, M. B., Weber, C. V.(eds.): CMM Capability Maturity ModelSM for Software. Version 1.1, Technical Report, CMU/SEI (1993)
[12] R.S. Pressman, Software Engineering: A Practitioner-s Approach, 3rd Ed., McGraw-Hill, New York, NY, 1992
[13] T. R. Gruber, A Translation Approach to Portable Ontologies, Knowledge Acquisition 5(2), pp. 199-220, June 1993
[14] W. J. Clancey, The Knowledge Level Reinterpreted: Modeling How System Interact, Machine Learning 4 (1989), pp. 285-291
[15] Zhanjun Li, Victor Raskin, and Karthik Ramani. (2007), A Methodology of Engineering Ontology Development for Information Retrieval, International Conference on Engineering Design, ICED-07. Paris, France. 28-31 August 2007.