Digital data is ubiquitous in contemporary culture: it documents environment, health, communication, government, arts, professional and private realms. For designers and practitioners data offers a profound opportunity to investigate, reveal and creatively represent this increasingly significant layer of our society.
This practical course grounds students in data as a key element in contemporary design practice, and in the design and production of data visualisations. Through a series of hands-on exercises students will develop static, dynamic and interactive representations of data for screen-based and tangible forms, and come to understand the functional and poetic dimensions of visualisation as a creative practice. The course introduces students to the cultures and contexts of data visualisation and design, and the analysis and interpretation of visualisations. It also introduces critical perspectives on the questions of representation and interpretation that are central to the field. This course will be of interest to students from a wide range of fields including design, fine arts, digital humanities and information technology, where the visual representation of data offers both immediate challenges and creative opportunities.
Upon successful completion, students will have the knowledge and skills to:
Upon successful completion of this course, students will have the knowledge and skills to:
- Source, handle and manage data for applications in visualisation.
- Create static, dynamic and interactive data visualisations using established techniques.
- Research and analyse data visualisation artefacts and cultures of practice.
- Respond to the cultural and technological contexts of data and visualisation design.
- Critically reflect on practice and substantiate design outcomes with research and rationale.
Indicative AssessmentVisualisation Techniques: Sketches and Exercises (30%) Learning Outcomes 1, 2
Visualisation Design Project (50%) Learning Outcomes 1-4
Research and Rationale, 1500 words (20%) Learning Outcomes 1-5
Assessment includes periodic critique and review sessions that provide formative feedback on work in progress.
Workload130 hours of total student learning time made up from:
a) 36 hours of contact comprising lectures, tutorials / workshops.
b) 94 hours of independent student research, reading and writing.
Requisite and Incompatibility
Ben Fry, Visualizing Data: Exploring and Explaining Data with the Processing Environment. O’Reilly Media, 2008.
Scott Murray, Interactive Data Visualization for the Web. O’Reilly Media, 2013.
Edward Tufte, The Visual Display of Quantitative Information. 2nd Ed. Graphics Press, 2008.
Toby Segaran, Jeff Hammerbacher. Beautiful Data: The Stories Behind Elegant Data Solutions. O’Reilly Media, 2009.
Assumed KnowledgeFamiliarity with basic computer programming techniques for graphics and design.
Tuition fees are for the academic year indicated at the top of the page.
If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
- Student Contribution Band:
- Unit value:
- 6 units