Glossary

AI (Artificial Intelligence). The discipline of building special computer systems that can perform complex activities usually only performed by humans.

Attribute. A quality or characteristic, e.g. weight, colour, usefulness.

Concepts. The individual items in a knowledge base, that represent things such as physical entities, people, tasks, issues, documents, etc.

Conceptual Knowledge. That part of expertise associated with the properties of concepts and the relationships between concepts. Also called ‘declarative knowledge’.

Consensus Session. A meeting held between a knowledge engineer and experts to resolve and/or document differences of opinion between experts.

Decision Support System. An AI system that provides advice and suggestions to a human user.

Domain. The subject area that a KA project is focused upon.

End-product. The deliverable from a KA project, such as a knowledge document, a knowledge web or an ontology.

End-users. The people or computer systems that use an end-product.

Expert. A person with substantial experience and expertise in a particular area, who is often the main source of knowledge for a KA project. Also called ‘domain expert’ or ‘subject matter expert’.

Expert System. An AI system that emulates the problem-solving capabilities of a human expert.

K-base (Knowledge Base). A special database that holds information representing the expertise of a particular domain.

KBE (Knowledge Based Engineering). The activity of creating software applications that incorporate the expertise of design engineers.

KBS (Knowledge Based System). An AI system that is filled with knowledge.

K-models (Knowledge models). Views of a knowledge base using diagrams and other structured representations, such as trees, maps, matrices and k-pages.

Knowledge Acquisition (KA). The activity of capturing, structuring and representing knowledge from any source for the purpose of storing, sharing or implementing the knowledge.

Knowledge Document. A document delivered by some KA projects that details the knowledge required to be coded into an intelligent software system, such as an expert system, a KBS or a KBE application.

Knowledge Elicitation. The activity of capturing knowledge from a human expert.

Knowledge Engineer. The role of a person within a KA project who performs most of the work, i.e. scopes and plans the project, interviews the experts, creates k-models and transforms the k-base into a useful end-product.

Knowledge Objects. The elements that make-up a k-base, i.e. concepts, relations, attributes and values.

Knowledge Programme. An initiative in an organisation that involves all of the KA activities and other knowledge-based activities.

Knowledge Support Team. A group of people that has experience in all aspects of KA whose roles include training and supporting knowledge engineers.

K-page. A structured page of text, images and hyperlinks that shows what is contained in the k-base about a particular concept. Also called ‘annotation page’.

Meta-model. A concept map showing all the main classes of concepts and relationships between them. Used for setting up a k-base ontology and templates.

Ontology. A structured representation or store of information that describes a body of knowledge and is often encoded in special computer formats (such as OWL).

OWL (Web Ontology Language). An XML format that adds meaning to the content of web files so that computer programs can read/use web-based resources.

Procedural Knowledge. The expertise required by a person or group of people to perform a complex process, task or activity.

Project Description Scheme. A framework for classifying and/or describing a particular project (e.g. by its properties, aims, deliverables). Used for planning and decision-making during a KA project.

Project Team. The people who perform activities on a KA project.

Role Sheet. A page of information describing the responsibilities and activities required of a specific role during a KA project (e.g. Expert Role Sheet, End User Role Sheet, Project Manager Role Sheet).

Scoping. The activity of selecting the specific areas of knowledge to be acquired during a KA project.

Triple. A relationship between two concepts, e.g. ‘book – written by – author’. So called, because there are three elements to the expression.

Value. A specific quality or characteristic of a concept, e.g. heavy, red, useful.

XML. A format for representing information in a web file. For example, rather than just have the word ‘car’ in a web file, the XML could hold extra (hidden) information such as: car is a vehicle, and car has the synonym ‘automobile’.