Overview
This course examines the theory, design, production, evaluation, and communication of data visualisations for research, policy, business, health, and public audiences. Students study visual perception and cognition, graphical encodings, data types and structures, exploratory and explanatory visualisation, chart selection, colour, scale, annotation, typography, layout, and small multiples.
The course addresses uncertainty and statistical communication, interactive dashboards, geographic and temporal displays, narrative sequencing, accessibility and inclusive design, misleading or distorted graphics, reproducible workflows, and communication across levels of technical expertise. Practical work uses code-based tools and dashboard platforms to transform raw data into publication-quality figures, briefing materials, and interactive products.
Students develop the ability to match visual form and narrative to audience, question, and medium; identify perceptual and statistical pitfalls; represent uncertainty and limitations honestly; create accessible static and interactive graphics; and provide concise interpretations supported by evidence.
Learning Outcomes
- Evaluate visualisations using principles of perception, cognition, graphical encoding, accessibility, and statistical integrity.
- Analyse data types, structures, uncertainty, and audience requirements to select appropriate visual forms and communication strategies.
- Design static and interactive visualisations that communicate evidence accurately across technical and non-technical contexts.
- Critique misleading, distorted, inaccessible, or statistically inappropriate graphics and justify corrective design decisions.
- Construct geographic, temporal, comparative, and multivariate displays using suitable scales, colour systems, annotations, typography, and layout.
- Synthesize visual narratives that connect exploratory analysis, explanatory sequencing, and audience-specific communication.
- Implement reproducible visualisation workflows that document data preparation, analytical decisions, code, and production processes.
- Evaluate visualisation products through evidence-based critique and revise them in response to audience, usability, and accessibility requirements.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Visualisation critique portfolio | 15.00% |
| Deliverable | Audience-specific communication brief | 20.00% |
| Assignment | Visual analytics portfolio | 25.00% |
| Capstone | Reproducible visualisation project | 30.00% |
| Test | Practical visualisation test | 10.00% |
Prerequisites
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.
