James H. Alexander, Michael J. Freiling, Sheryl J. Shulman, Jeffery L. Staley, Steven Rehfuss, Steven L. Messick
Knowledge engineering suffers from a lack of formal tools for understanding domains of interest. Current practice relies on an intuitive, informal approach for collecting expert knowledge and formulating it into a representation scheme adequate for symbolic processing. Implicit in this process, the knowledge engineer formulates a model of the domain, and creates formal data structures (knowledge base) and procedures (inference engine) to solve the task at hand. Newell (1982) has proposed that there should be a knowledge level analysis to aid the development of AI systems in general and knowledge-based expert systems in particular. This paper describes a methodology, called ontological analysis, which provides this level of analysis. The methodology consists of an analysis tool and its principles of use that result in a formal specification of the knowledge elements in a task domain.