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COMP40610

Academic Year 2025/2026

Information Visualisation (COMP40610)

Subject:
Computer Science
College:
Science
School:
Computer Science
Level:
4 (Masters)
Credits:
5
Module Coordinator:
Dr Anh Vu Vo
Trimester:
Autumn
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

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 artifact 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 visualsiation addressing both practical and theoretical concerns. Specific tools for creating data visualsiations are also explored.

About this Module

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
Autonomous Student Learning

75
Lectures

24
Practical

24
Total

123

Approaches to Teaching and Learning:
- Lectures
- Labs
- In class group activities
- In class activities
- In class group discussion
- Assigned reading
- Assignments

If students are permitted to use generative AI tools in assignments, that will be indicated in the assignment specification.

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 , COMP47970 - Information Visualisation BD


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade Component repeat (in-module) Offered
Assignment(Including Essay): Use Tableau to create a series of charts to answer defined questions. Week 3 Alternative linear conversion grade scale 40% No
0
 No
Assignment(Including Essay): Implement a "dashboard" style interactive visualisation in Vega-Lite, using the Vega-Lite functionality that is covered in the labs. Week 7 Alternative linear conversion grade scale 40% No
0
 No
Assignment(Including Essay): An assignment to design and create an interactive visualisation tool that enables the exploration and analysis of a complex quantitative dataset. Week 9 Alternative linear conversion grade scale 40% No
60
 No
Exam (In-person): A timed in-class, closed book, test. including multiple choice questions, short answer questions, and some longer form questions, covering all topics on the module. Week 12 Alternative linear conversion grade scale 40% No
40
 No

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.


Carry forward of passed components
Yes
 

Resit In Terminal Exam
Spring 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
Narod Kebabci Tutor
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