Undergraduate Course: Knowledge Modelling and Management (Level 10) (INFR10020)
||School of Informatics
||College of Science and Engineering
||Available to all students
|Credit level (Normal year taken)
||SCQF Level 10 (Year 4 Undergraduate)
|Home subject area
||Other subject area
||Taught in Gaelic?
||This course addresses knowledge management through knowledge modelling techniques. It provides an introduction to the different types of knowledge modelling methods and explains how knowledge may be described in conceptual models to provide a foundation to support reasoning within modern organisations and to help them carry out tasks. 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.
|| It is RECOMMENDED that students have passed
Logic Programming (INFR09031)
|| Students MUST NOT also be taking
Knowledge Modelling and Management (Level 11) (INFR11072)
|| Successful completion of Year 3 of an Informatics Single or Combined Honours Degree, or equivalent by permission of the School. Knowledge Representation and Inference and Logic Programming are preferred but not strictly pre-requisite.
Information for Visiting Students
|Displayed in Visiting Students Prospectus?
Course Delivery Information
|Delivery period: 2011/12 Semester 2, Available to all students (SV1)
||WebCT enabled: No
|Central||Lecture||1-11|| 16:10 - 17:00|
|Central||Lecture||1-11|| 16:10 - 17:00|
||First class information not currently available|
|Main Exam Diet S2 (April/May)||2:00|
Summary of Intended Learning Outcomes
|1 - To understand the principles of ontology design;
2 - To be able to construct an ontology and understand the formal basis of the definitions it contains;
3 - To understand the issues of sharing knowledge in an organisational context and in a scientific community;
4 - To gain an overview of the different types of knowledge modelling methods and how they may be used together;
5 - To be able to select the appropriate modelling method(s) given certain circumstances;
6 - To be able to construct correct models given a domain;
7 - To be able to carry out reasoning on models based on lightweight logical methods;
|Written Examination 75
Assessed Assignments 25
Oral Presentations 0
This course will involve systems building tasks in addition to learning modelling methods. Coursework will include practical exercises on realistic knowledge engineering scenarios.
If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
||The following are core elements of the syllabus:
1. Knowledge sharing and the knowledge life-cycle:
*Methodology for ontology building and introduction to Protege;
*Description Logic and OWL (Web Ontology Language) with a brief introduction to RDF syntax;
*Axiomatic approaches to ontology;
*Philosophical views of ontology;
*Example ontologies and their uses (Gene Ontology, Cyc);
*Evaluation criteria for ontologies.
2. Knowledge management and modelling methods:
*Overview: an introduction to knowledge management and how (semi-formal) knowledge modelling and engineering techniques can contribute to this field;
*Knowledge acquisition and model building techniques;
*An advanced introduction to the different modelling methods: Organisational Models from CommonKADS, IDEF Process Model, UML Class Diagram, ontology, knowledge management application case study.
*An introduction to the different modelling methods: Organisational Models from CommonKADS, IDEF Process Model, UML Class Diagram, Relational Data Model and ontology.
*Formalisation and knowledge representation techniques related to representing (semi-formal) models;
*Automated support for building, critiquing and reasoning on models;
*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
||Knowledge Engineering and Management: The CommonKADS Methodology. Guus Schreiber, Robert de Hoog, Hans Akkermans, Anjo Anjewierden, Nigel Shadbolt, Walter Van de Velde.
Timetabled Laboratories 0
Non-timetabled assessed assignments 30
Private Study/Other 50
||Dr Amos Storkey
Tel: (0131 6)51 1208
||Miss Kate Weston
Tel: (0131 6)50 2701
copyright 2011 The University of Edinburgh -
3 April 2011 11:20 am