Article,
Knowledge engineering: Principles and methods
Data & Knowledge Engineering, 25 (1-2): 161--197 (March 1998)
Abstract
This paper gives an overview of the development of the field of Knowledge Engineering over the last 15 years. We discuss the paradigm shift from a transfer view to a modeling view and describe two approaches which considerably shaped research in Knowledge Engineering: Role-limiting Methods and Generic Tasks. To illustrate various concepts and methods which evolved in recent years we describe three modeling frameworks: CommonKADS, MIKE and PROTÉGÉ-II. This description is supplemented by discussing some important methodological developments in more detail: specification languages for knowledge-based systems, problem-solving methods and ontologies. We conclude by outlining the relationship of Knowledge Engineering to Software Engineering, Information Integration and Knowledge Management.
Tags
- 68t30-knowledge-representation
- conceptual
- dblp
- engineering
- imported
- jabref:nokeywordassigned
- knowledge
- knowledge-engineering
- knowledge-management
- knowledge_engineering
- linked_data
- methods
- mgraube
- modeling
- ontologies
- ontology
- principles
- wp4
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- @mgraube 12 years ago (last updated 12 years ago)Definition Ontology (page 25): An ontology is a formal, explicit specification of a shared conceptualisation. A ‘conceptualisation’ refers to an abstract model of some phenomenon in the world by having identified the relevant concepts of that phenomenon. ‘Explicit’ means that the type of concepts used, and the constraints on their use are explicitly defined. For example, in medical domains, the concepts are diseases and symptoms, the relations between them are causal and a constraint is that a disease cannot cause itself. ‘Formal’ refers to the fact that the ontology should be machine readable, which excludes natural language. ‘Shared’ reflects the notion that an ontology captures consensual knowledge, that is, it is not private to some individual, but accepted by a group.