This paper responds to an increasing interest in how data-driven interactive artworks can support a greater understanding of the relationship between humans and data. This paper extends this work by focusing on the  The Prediction Machine , an interactive and data-driven artwork that arose from collaborations between an artist, climate scientists, HCI researchers and the wider public. A study of the practice-led process reveals: (a) how the artist "performed" scientific data across multiple outputs; (b) how the artist walked a line between scientific and artistic process; (c) how the public experienced data across multiple components of the artwork; (d) how the artwork can be seen as process rather than a exhibition or artifact; and (e) how tensions between artistic strategies and scientific processes inherent in the creation of data-driven artworks might inform future work involving public engagement with scientific data.
['Rachel Jacobs', 'Steve Benford', 'Ewa Luger', 'Candice Howarth']
The Prediction Machine: Performing Scientific and Artistic Process