Knowledge Modelling and Management (Level 11) (P01196)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : INF-P-KMM

This course provides an introduction to the different types of knowledge modelling methods and explains how knowledge may be described in conceptual models - in order to provide a foundation to support reasoning within modern organisations and to help them carry out tasks. This course will then equip students with advanced knowledge modelling techniques that support knowledge management. The course will emphasise the design and uses of models: examples are ontologies, organisational and process models. It will also cover formal techniques for representation and reasoning with such knowledge. The advanced elements are the ability to analyse and critically review computational models of knowledge.

Entry Requirements

? Pre-requisites : For Informatics PG students only, or by special permission of the School. Fundamentals of Artificial Intelligence and Logic Programming are preferred but not strictly pre-requisite.

? Prohibited combinations : Knowledge Modelling & Management (Level 10)

Subject Areas

Home subject area

Knowledge Representation and Reasoning, (School of Informatics, Schedule O)

Other subject areas

Net-Centric Computing, (School of Informatics, Schedule O)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

First Class Information

Date	Start	End	Room	Area	Additional Information
07/01/2008	16:10	17:00	Room G.10, William Robertson Building	Central

All of the following classes

Type	Day	Start	End	Area
Lecture	Monday	16:10	17:00	Central
Lecture	Thursday	16:10	17:00	Central

Summary of Intended Learning Outcomes

-To understand the principles of ontology design;
-To be able to construct an ontology and understand the formal basis of the definitions it contains;
-To be able to apply evaluation criteria to assess ontologies;
-To understand the issues of sharing knowledge in an organisational context and in a scientific community;
-To gain an overview of the different types of knowledge modelling methods and how they may be used together;
-To be able to select the appropriate modelling method(s) given certain circumstances;
-To be able to construct correct models given a domain;
-To be able to carry out reasoning on models based on lightweight logical methods;
-To acquire the ability to critically review relevant literature independently thus extend one's knowledge.
-To solve problems of a more open-ended nature.
-To critically appraise the strengths and weaknesses of knowledge-based models.