COMP47970 Information Visualisation (Blended Delivery)

Academic Year 2023/2024

This module is suitable for students interested in the fundamental and practical underpinnings of Information Visualisation. Information Visualisation is a research area that focuses on the use of graphical techniques to present data in an explicit form. Such static or dynamic presentations (pictures) help people formulate an understanding of data and an internal model of it for reasoning about. Such pictures of data are an external artefact supporting decision making. While sharing many of the same goals of Scientific Visualisation, Human Computer Interaction, User Interface Design and Computer Graphics, Information Visualisation focuses on the visual presentation of data without a physical or geometric form. As such it relies on research in mathematics, data mining, data structures, algorithms, graph drawing, human-computer interaction, cognitive psychology, semiotics, cartography, interactive graphics, imaging and visual design.

This module explores the most important topics in information visualisation addressing both practical and theoretical concerns. Specific tools for creating data visualsiations are also explored.

Show/hide contentOpenClose All

Curricular information is subject to change

Learning Outcomes:

On completion of this module, the learner will be able to

1. Demonstrate an understanding of human visual perception & how it can be exploited to design effective visualisations
2. Identify visualisation approaches suitable for specific data types (including tabular data, spatial data, and network data).
3. Critically evaluate different visualisation approaches as applied to particular tasks
4. Implement interactive visualisation approaches using a programming language
5. Design experiments to test the effectiveness of a specific visualisation approach

Student Effort Hours: 
Student Effort Type Hours
Laboratories

16
Autonomous Student Learning

75
Online Learning

22
Total

113
Approaches to Teaching and Learning:
Lectures
Labs
Peer assessment
Assigned reading
Assignments
Online activities 
Requirements, Exclusions and Recommendations
Learning Requirements:

Prior knowledge of a specific programming language is not required. However all students must be comfortable programming in some language (e.g. R/Python/Java/C). Students should also be able to use a text editor to edit code.


Module Requisites and Incompatibles
Incompatibles:
COMP30750 - Information Visualisation -DS , COMP40610 - Information Visualisation


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Assignment: Information visualisation assignment Unspecified n/a Graded No

60
Examination: In person exam (on paper).

This will contain MCQs, Short Answer Questions, and some longer form questions.		 1 hour End of Trimester Exam No Graded No

40

Carry forward of passed components
Yes
 
Resit In Terminal Exam
Autumn No
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Diptasree Debnath Tutor
Narod Kebabci Tutor
Crisron Rudolf Lucas Tutor
Mr Anjan Venkatesh Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
 
Spring
      
Laboratory Offering 1 Week(s) - 21, 22, 23, 24, 25, 26, 30, 31, 32 Thurs 10:00 - 11:50
Laboratory Offering 1 Week(s) - 29 Thurs 10:00 - 11:50
External & School Exams Offering 1 Week(s) - 33 Thurs 10:00 - 11:50
Spring