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MSc: Knowledge Management

Index

Module Description MSc (level 11) UG4 (level 10)

Module Notes and Timetable

Tutorials

Lecture Slides

Assessed Assignment

Lecturer

Jessica Chen-Burger 7.08 Appleton Tower Email: jessicac @ aiai.ed.ac.uk and
Stuart Aitken 7.09 Appleton Tower, Tel: 6502738, Email: stuart @ aiai.ed.ac.uk

Course:   Knowledge Modelling and Management (Level 11)

Course Web page

Credit Points	10
Credit Level	11
Acronym	INF-5-KMM
Study Pattern	Study Format		Hours
	Lectures		20
	Tutorials		0
	Timetabled Laboratories		0
	Non-timetabled assessed assignments		30
	Private Study/Other		50
	Total		100

Pre-requisite Courses	None
Other Pre-requisite Requirements	Fundamentals of Artificial Intelligence and Logic Programming are preferred but not strictly pre-requisite.
Co-requisites/Forbidden Combinations	None

Short Description

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.

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.

Assessment Weightings (%)	Assessment		%
	Written Examination		75
	Assessed Assignments		25
	Oral Presentations		0

Assessed Coursework

This course will involve systems building tasks in addition to learning modelling methods. Coursework will include practical exercises on realistic knowledge engineering scenarios. At the advanced level, these will involve structured reviews and assessments of designs and solutions.

Syllabus

The following are core elements of the syllabus:

Knowledge sharing and the knowledge life-cycle:

1. Methodology for ontology building and introduction to Protege;
2. Description Logic and OWL (Web Ontology Language) with a brief introduction to RDF syntax;
3. Axiomatic approaches to ontology;
4. Philosophical views of ontology;
5. Example ontologies and their uses (Gene Ontology, Cyc);
   
6. Evaluation criteria for ontologies.
   

Knowledge management and modelling methods:

1. Overview: an introduction to knowledge management and how (semi-formal) knowledge modelling and engineering techniques can contribute to this field;
2. Knowledge acquisition and model building techniques;
3. An introduction to the different modelling methods: Organisational Models from CommonKADS, IDEF Process Model, UML Class Diagram, Relational Data Model and ontology.
4. Formalisation and knowledge representation techniques related to representing (semi-formal) models;
5. Automated support for building, critiquing and reasoning on models;
6. Knowledge publishing: take a look at current semantic web languages and see how they are related to knowledge management and enterprise/conceptual modelling methods.
   

Relevant QAA Computing Curriculum Sections:  Artificial Intelligence

Reading List

Knowledge Engineering and Management: The CommonKADS Methodology. Guus Schreiber, Robert de Hoog, Hans Akkermans, Anjo Anjewierden, Nigel Shadbolt, Walter Van de Velde, and Bob Wielinga (1999)

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Last updated   10 March 2005   by   Stuart Aitken