The course is a combined theory and practice exploration of creative data visualization methods through the lens of critical data questions. We will address issues of data equity, bias, privacy, and colonialism, whilst exploring an array of visualization techniques, including experimentation with immersive data visualization through extended reality technology. We will explore emerging critical data frameworks that look at data feminism, the ethics of machine learning, decolonizing data, and data humanism. We will look at the work of artists, designers, and activists and analyze their visual strategies and practice-based approaches. Students will gain critical insight and creative data techniques to use in their future work.

Course Requirements:

The course requires regular participation in lectures, discussions, and active involvement in tutorial-led practice components. Students will write weekly responses to class readings, and develop a final paper and visual project that together explore a praxis-based approach to their chosen critical data topic.

Intended Audience:

This course is accessible to all undergraduate students at all levels, including those without experience in art, design, or data methods. Students who are interested in both asking critical questions, and exploring creative approaches to the representation of data are encouraged to take this class.