- One Semester or Equivalent
- 48 hours face to face + blended
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
Higher Ed. Semester 2
Last self enrolment:
Last withdraw without fail:
Concurrent Pre-requisite (completed prior or at same time)
Aims and objectives
This unit aims to instruct students on the fundamental principles of information visualisation, and good design practices. Students will explore a wide range of visualisation idioms and develop the ability to create visualisations that empower users to understand real-world data sets.
Unit Learning Outcomes (ULO)
On successful completion of this unit students will be able to:
1 Critically evaluate data visualisations and propose improvements based on an understanding of human perception and cognition and data visualisation design principles
2 Apply a structured design process to create effective visualisations within a research context
3 Create interactive data visualisations using real-world data sets
4 Effectively communicate and reflect on the design process for an interactive visualisation, including the choice of visualisation idioms and reasoning behind design decisions
Unit information in detail
- Teaching methods, assessment and content.
Hours per week
Number of Weeks
On Campus Lecture
|On Campus Class in Computer Lab||2||12||24|
Unspecified Activities Independent Learning
Unit Learning Outcomes (ULOs)
1, 2, 3, 4
|Research and Tech Report||Individual||30-45%||1,3,4|
As the minimum requirements of assessment to pass the unit, a student must achieve:
i) An overall grade of 50% or more.
ii) At least 40% in the Research report.
Students who do not achieve (ii) will receive a maximum of 45% as the total mark for the unit
- Introduction to data visualisation
- Brief history of data visualisation
- Data visualisation design guidelines, graphical integrity
- Visual variables: marks and channels
- Visualisation critique
- Analysis of user tasks in visualisation usage
- Introduction to Data Driven Documents (D3)
- Data sets and types
- Interaction: Manipulating view, Filtering
- Data visualisation idioms
- Colour theory
- Human perception and cognition
- Introduction to data visualisation research
- Reading materials.
A list of reading materials and/or required texts will be made available in the Unit Outline.