COMP6234 Data Visualisation
Module Overview
Welcome to the Data Visualisation module! In this course, you would learn about the terminology, concepts and techniques behind visualising data, and will get to use a range of tools to get experience of creating visual representations of data. You will gain an understanding of how humans perceive data, and why certain techniques can greatly enhance the effectiveness of any visualisation. We will look at example images to critique them, building up knowledge about what works, and what doesn't. The course will include a mix of lectures, tutorials, seminars and hands-on exercises.
Aims and Objectives
Module Aims
To become familiar with core data visualisation approaches and tools
Learning Outcomes
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Key concepts in data science, including tools, approaches and application scenarios
- Topics in information design
- Topics in interaction design and user engagement
- State-of-the-art tools to build useful visualisations for different types of data sets and application scenarios
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Understand and apply the fundamental concepts and techniques in data visualisation
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Solve specific real-world problems related to the visualisation and interpretation of data analysis results
Syllabus
Fundamentals of data visualisation and storytelling - History of data visualisation - Planning a visualisation - Types of data stories and principles to design them - Types of charts and how to choose them - Bad design and lying with statistics - Visual insights: relations and structures - Visual perception and information design for the mind - Interactive visualisations - Online tools and technologies (e.g., Tableau, D3)
Learning and Teaching
Teaching and learning methods
Lectures and tutorials. Assessment via coursework (exercises, technical report) and exam.
| Type | Hours |
|---|---|
| Preparation for scheduled sessions | 9 |
| Lecture | 18 |
| Completion of assessment task | 67 |
| Tutorial | 18 |
| Follow-up work | 9 |
| Wider reading or practice | 29 |
| Total study time | 150 |
Assessment
Summative
| Method | Percentage contribution |
|---|---|
| Individual project | 100% |
Referral
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Repeat Information
Repeat type: Internal & External