Core modules
Visualisation Foundations
Data visualisations (graphs, maps, networks) have become a fundamental currency for the exploration of data and the exchange of information. This module develops foundational understanding in what visualisations are and how they operate. Coding skills are developed alongside the conceptual understanding, allowing students to develop visualisations and their understanding in terms of design, theory, data and code.
As visualisation is such an interdisciplinary topic, students will engage with diverse topics spanning data science and psychology, graphic design and the arts, and critical cartography and data feminism.
Data Visualisation in Science, Culture and Public Policy
The module introduces concepts, methods and empirical cases that enable an understanding of the affordances, power and limitations of data visualisation in science, culture, and public policy.
Data visualisations have opened-up diverse challenges and opportunities for contemporary science, culture and public policy that show how visualisations mediate knowledge and enable communications through persuasion and real-world engagements. The module draws from social, cultural and political theory, science and technology studies, as well as digital and environmental humanities, equipping students with an ability to analyse and research the affordances of data visualisation as forms of knowledge, intervention and participation.
Advanced Visualisation Design Labs
In this module, students develop three visualisation projects that further advance their independence in visualisation design, development, analysis and critique. Each project responds to a visualisation challenge drawn from methodological, societal, scientific and policy topics. At least one of the challenges involves a real-world problem proposed by an external partner.
Students respond to project briefs through hands-on workshops, prototyping, and expanding their design and technical skills in dialogue with their methodological and critical understanding. Master-classes expand students’ methodological and technical repertoire in areas such as human-centred design, typography, storytelling, stencilling, and digital cartography. In dialogue with their visualisation portfolio, students produce a design manifesto exploring their methodological and aesthetic approach, in relation to ethics and visual cultures.
Optional modules
Optional modules can vary from year to year. Example optional modules may include:
- Data Science Across Disciplines: Principles, Practice and Critique
- User Interface Cultures: Design, Method and Critique
- Generative AI: Histories, Techniques, Cultures and Impacts
- Urban Data
- Interdisciplinary Approaches to Machine Learning
- Media Activism
- Approaches to the Digital
- Complexity in the Social Sciences
- Digital Objects, Digital Methods
- Big Data Research: Hype or Revolution?
