Data Visualisation
Duration
- One Semester or Equivalent
Contact hours
- 48 hours
On-campus unit delivery combines face-to-face and digital learning.
2022 teaching periods
Hawthorn
| Higher Ed. Semester 2 | ||
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
OR
Concurrent Pre-requisite
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 | |
|---|---|
| On successful completion of this unit students will be able to: | |
| # | Unit Learning Outcome Description |
| ULO1 | Critically evaluate data visualisations and propose improvements based on an understanding of human perception and cognition and data visualisation design principles |
| ULO2 | Apply a structured design process to create effective visualisations within a research context |
| ULO3 | Create interactive data visualisations using real-world data sets |
| ULO4 | 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.
Teaching methods
| All Applicable Locations | |||||
|---|---|---|---|---|---|
| Activity Type | Activity | Total Hours | Number of Weeks | Hours Per Week | Optional - Activity Details |
| Face to Face Contact | Lecture | 24 | 12 weeks | 2 | No Description |
| Face to Face Contact | Tutorials in Computer Labs | 24 | 12 weeks | 2 | No Description |
| Unspecified Learning Activities | Independent Learning | 102 | 12 weeks | 8.5 | No Description |
| Total Hours: | 150 | Total Hours (per week): | 12.5 | ||
Assessment
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Content
- 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
Study resources
- References.
References
A list of reading materials and/or required texts will be made available in the Unit Outline.