DataRemix: Designing The Datamade Through ArtScience Collaboration

Ruth West,Roger Malina,John Lewis,Scot Gresham-Lancaster, Alejandro Borsani, Brian Merlo,Lifan Wang

semanticscholar(2013)

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摘要
ArtScience is emerging as one approach for creating novel ways of seeing and new ways of knowing. We propose a role for ArtScience research and creative work in contributing to the necessary shifts to go beyond the current crisis of representation. We specifically describe DataRemix, a recombination and reappropreation practice intended to trigger novel subjective experiences and associations. The narratives framing data creation and representation circumscribe what we can see and know, and how we see and know. How do we see and know beyond what our instruments, algorithms, representational schemas and training guide us to see and know? How do we look for what we don’t know we’re looking for when we can only examine at most a tiny fraction of the available data? Our argument is grounded in and will be illustrated by experience with several ArtScience collaborations spanning genomics, astrophysics, new media, and holographic sound design.
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