ABSTRACT
This chapter departs from the premise that we do not really know how to imagine big data as a new medium while the aesthetic preconditions for such knowledge remain underexplored. It focuses on a particular class of images: oceanic ones. The first section explains this choice. The second section considers this problem: for all their epistemic depth and sophistication, contemporary data analytic methods are often aesthetically shallow. The section that follows considers an inverse problem of the depths of apparent superficiality: one way to enrich how we feel, sense, and imagine our way around a problem like that of big data, I argue, is to understand the images that typically mediate experience of it, not as superficial clichés or ‘mere metaphors’, but as potentially instructive media in their own right. The final section concludes with an argument for an ‘oceanic’ aesthetics. Thinkers engaged throughout include Floridi, Dean, Deleuze, and Leibniz.
