The Spiral_OWL Model – Towards Spiral Knowledge Engineering
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.
[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.
[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.
@article{"International Journal of Information, Control and Computer Sciences:56757", author = "Hafizullah A. Hashim and Aniza. A", title = "The Spiral_OWL Model – Towards Spiral Knowledge Engineering", 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.", volume = "4", number = "2", pages = "251-6", }