Knowledge engineering (KE) refers to all technical, scientific and social aspects involved in building, maintaining and using
knowledge-based systems
A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. The term is broad and refers to many different kinds of systems. The one common theme that unites all knowledge based systems i ...
.
Background
Expert systems
One of the first examples of an
expert system
In artificial intelligence, an expert system is a computer system emulating the decision-making ability of a human expert.
Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if� ...
was
MYCIN, an application to perform medical diagnosis. In the MYCIN example, the domain experts were medical doctors and the knowledge represented was their expertise in diagnosis.
Expert systems were first developed in artificial intelligence laboratories as an attempt to understand complex human decision making. Based on positive results from these initial prototypes, the technology was adopted by the US business community (and later worldwide) in the 1980s. The Stanford heuristic programming projects led by
Edward Feigenbaum was one of the leaders in defining and developing the first expert systems.
History
In the earliest days of expert systems there was little or no formal process for the creation of the software. Researchers just sat down with domain experts and started programming, often developing the required tools (e.g.
inference engine
In the field of artificial intelligence, an inference engine is a component of the system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert ...
s) at the same time as the applications themselves. As expert systems moved from academic prototypes to deployed business systems it was realized that a methodology was required to bring predictability and control to the process of building the software. There were essentially two approaches that were attempted:
# Use conventional software development methodologies
# Develop special methodologies tuned to the requirements of building expert systems
Many of the early expert systems were developed by large consulting and system integration firms such as
Andersen Consulting. These firms already had well tested conventional
waterfall methodologies (e.g. Method/1 for Andersen) that they trained all their staff in and that were virtually always used to develop software for their clients. One trend in early expert systems development was to simply apply these waterfall methods to expert systems development.
Another issue with using conventional methods to develop expert systems was that due to the unprecedented nature of expert systems they were one of the first applications to adopt
rapid application development
Rapid application development (RAD), also called rapid application building (RAB), is both a general term for adaptive software development approaches, and the name for James Martin's method of rapid development. In general, RAD approaches to ...
methods that feature iteration and prototyping as well as or instead of detailed analysis and design. In the 1980s few conventional software methods supported this type of approach.
The final issue with using conventional methods to develop expert systems was the need for
knowledge acquisition. ''Knowledge acquisition'' refers to the process of gathering expert knowledge and capturing it in the form of rules and ontologies. Knowledge acquisition has special requirements beyond the conventional specification process used to capture most business requirements.
These issues led to the second approach to knowledge engineering: development of custom methodologies specifically designed to build expert systems. One of the first and most popular of such methodologies custom designed for expert systems was the
Knowledge Acquisition and Documentation Structuring Knowledge Acquisition and Documentation Structuring (KADS) is a structured way of developing knowledge-based systems (expert systems). It was developed at the University of Amsterdam
The University of Amsterdam (abbreviated as UvA, nl, Univers ...
(KADS) methodology developed in Europe. KADS had great success in Europe and was also used in the United States.
See also
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Knowledge level modeling Knowledge level modeling is the process of theorizing over observations about a world and, to some extent, explaining the behavior of an agent as it interacts with its environment.
Crucial to the understanding of knowledge level modeling are Allen ...
*
Knowledge management
Knowledge management (KM) is the collection of methods relating to creating, sharing, using and managing the knowledge and information of an organization. It refers to a multidisciplinary approach to achieve organisational objectives by making ...
*
Knowledge representation and reasoning
*
Knowledge retrieval Knowledge retrieval seeks to return information in a structured form, consistent with human cognitive processes as opposed to simple lists of data items. It draws on a range of fields including epistemology (theory of knowledge), cognitive psycholo ...
*
Knowledge tagging
In information systems, a tag is a keyword or term assigned to a piece of information (such as an Internet bookmark, multimedia, database record, or computer file). This kind of metadata helps describe an item and allows it to be found agai ...
*
Method engineering
Method engineering in the "field of information systems is the discipline to construct new methods from existing methods".F. Harmsen & M. Saeki (1996). "Comparison of four method engineering languages". In: Sjaak Brinkkemper et al. (eds.) ''P ...
References
External links
Data & Knowledge Engineering– Elsevier Journal
Knowledge Engineering Review Cambridge Journal
– World Scientific
Expert Systems: The Journal of Knowledge Engineering– Wiley-Blackwell
{{DEFAULTSORT:Knowledge Engineering
Semantic Web
Ontology (information science)