The University of Southampton
Courses

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 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
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

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.

TypeHours
Tutorial18
Lecture18
Follow-up work9
Wider reading or practice29
Preparation for scheduled sessions9
Completion of assessment task67
Total study time150

Assessment

Summative

MethodPercentage contribution
Individual project 100%

Referral

MethodPercentage contribution
Coursework 100%

Repeat Information

Repeat type: Internal & External

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