Data Visualisation
Duration
- One Semester or Equivalent
Contact hours
- 48 hours face to face + blended
On-campus unit delivery combines face-to-face and digital learning.
2023 teaching periods
| Hawthorn Higher Ed. Semester 2 |
||
|---|---|---|
Dates: Results: Last self enrolment: Census: Last withdraw without fail: |
Prerequisites
OR
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.
Teaching methods
Hawthorn
Type | Hours per week | Number of Weeks | Total |
On Campus Lecture | 2 | 12 | 24 |
| On Campus Class in Computer Lab | 2 | 12 | 24 |
Unspecified Activities Independent Learning | 8.5 | 12 | 102 |
TOTAL | 150 hours |
Assessment
Types | Individual/Group Role | Weighting | Unit Learning Outcomes (ULOs) |
Assignment | Individual | 10-20% | 1 |
| Class Exercises | Individual | 10-20% | 2,3,4 |
Project | Individual | 30-45% | 1, 2, 3, 4 |
| Research and Tech Report | Individual | 30-45% | 1,3,4 |
Hurdle
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
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
- Reading materials.
Reading materials
A list of reading materials and/or required texts will be made available in the Unit Outline.