Knowledge Graphs for AI Systems

Module overview

The last decade and a half have seen the Web move away from a purely document-centric information system to one in which hypertext techniques are applied to the sort of data found in databases; the term “Semantic Web” is used to refer to this Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, write rules for handling data, and develop systems that can support trusted interactions over the network. This module looks at the development of the Semantic Web, at the technologies underlying it, and at the way in which those technologies are applied.

Aims and Objectives

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

Isolate and organise conceptual elements of simple domains of discourse
Critically evaluate developments on the Semantic Web
Relate methodologies and techniques to a range of practical applications

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

The technical architecture of the Semantic Web, and its integration with the World Wide Web
The underlying knowledge representation formalisms in use on the Semantic Web
The Linked Web of Data
Common application vocabularies in use on the Semantic Web
Common ontology design patterns

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

Use common Semantic Web tools to design, implement, document and verify ontologies

Learning and Teaching

Teaching and learning methods

Lectures and Tutorials

Study time
Type	Hours
Wider reading or practice	43
Follow-up work	18
Revision	10
Tutorial	12
Completion of assessment task	13
Lecture	36
Preparation for scheduled sessions	18
Total study time	150

Resources & Reading list

Textbooks

Hebeler, J., Fisher, M., Blace, R. and Perez-Lopez, A (2009). Semantic Web Programming. Wiley..

Assessment

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Final Assessment	75%
Continuous Assessment	25%

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Breakdown
Method	Percentage contribution
Set Task	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Set Task	100%

Repeat Information

Repeat type: Internal & External