Cognitive informatics: a knowledge engineering perspective

Abstract

This paper presents knowledge engineering and development of an ontology for structuring the knowledge base of an expert system. Ontological engineering is a process that facilitates construction of the knowledge base of an intelligent system, which can be defined as a computer program that can duplicate problem-solving capabilities of human experts in specific areas. In this case, the system can automate the operator's experiences in monitor and control an oil production and processing facility. Ontology is the study of the organization and classification of knowledge. Ontological engineering in artificial intelligence (AI) has the practical goal of constructing frameworks for knowledge that allow computational systems to tackle knowledge-intensive problems and supports knowledge sharing and reuse. We present in this paper the processes of knowledge acquisition (KA), analysis, and representation using a conceptual modeling tool, the inferential modeling technique (IMT), as a basis for ontology construction in the domain of monitoring of a petroleum production and processing facility. The objectives of developing an expert system for the oil production facility are to enable remote monitoring of the important processing parameters in different sections of the facilities and facilitate generation of operational and management reports from the gathered data for the petroleum production facility located in Saskatchewan, Canada.