[-empyre-] Data Visualization and Decelerationist Aesthetics
kb at katherinebehar.com
Tue Jul 12 02:43:11 AEST 2016
Thank you everyone for the insightful discussion last week and thank you Christina for the invitation to participate here.
As is customary, I'd like to introduce a bit about me and my work for context. I make art and write about feminism and labor issues in digital culture. My background is in performance art, so performing bodies, human or nonhuman, are at the core of my thinking. I try to create solidarities between all kinds of such bodies, which I feel are universally—if unevenly—exploited in contemporary capitalism. My work on Object-Oriented Feminism takes up such ideas of nonanthropocentrism and solidarities among “feminist objects” (to borrow Irina Aristarkhova’s term) [See: https://www.upress.umn.edu/book-division/books/object-oriented-feminism].
The overwhelming backdrop for all of my work (both art and writing) is what I view as a grossly out of balance drive toward overproduction. My work explores elements of technology and digital culture that throttle down speed and resist that march to ever greater productivity. Instead, I look to redundancies and resistances built into media ecosystems. I’ve defined “decelerationist aesthetics” to refer to work in which “the aesthetic properties, proclivities, and performances of objects come to defy the accelerationist imperative to be nimbly individuated.”
Christina invited my participation here around my first inquiry toward decelerationist aesthetics, my recent essay chapbook, _Bigger than You: Big Data and Obesity_, [See: https://punctumbooks.com/titles/bigger-than-you-big-data-and-obesity/]. In Bigger than You, I discuss big data (here specifically, personally-identifiable, human-produced data) and obesity as forms of overproduction of self. Extrapolating from the work of Lauren Berlant and Elizabeth Grosz, I question how excess self blurs lines between self and other, or person and population, offering a possible alternative to identity politics and its focus on the individual—a unit that I worry is too vulnerable under neoliberalism.
But, perhaps another essay on decelerationist aesthetics, called “‘Seeing Things’ in Data Visualization” (forthcoming in the fall), hews more closely to this discussion. In “Seeing Things,” I make two strong claims. First, I argue that data visualization is totally contingent. If we consider data definitionally as the "raw measure" of the world as “given,” then data visualization is a contradiction in terms; the "visualization” turns data into information, which is to say something processed beyond raw measurement. Drawing from work by Alex Galloway and Vilém Flusser, I believe that this tenuous connection to data means visualizations can take any form.
*Here there are some resonances with last week’s discussion about representation.
From this follows my second claim, namely that data visualization (especially because it is contingent and can be done endlessly) participates in the dominant logic of overproduction, just like almost everything else in today’s culture. Although visualizations are a form of “data reduction” in that they simplify raw data into generalized patterns, they are also productive, or to use Catherine’s term, generative, in their own right.
*Here I wonder, how does this fit with Catherine’s distinction between dat vis critique and generative data vis? I think all data visualization is generative, and I’m concerned about that because I feel that we don’t need *more* of anything right now; if I may use the royal “we” are already producing too much, too quickly, I think.
I’ll end here with an example from my art, something I’m currently working on. I consider this a sculpture, but perhaps it is a visualization of data in a different sense. “Data Cloud (A Heap, A Mass, A Rock, A Hill)” is a malleable form, covered in over 6000 QWERTY keyboard keys, which represent individual data points. I’m drawing on early meanings of “data” and “cloud”. The first English usage of the word “data” was in the phrase “a heap of data” from the 1600s. The term “cloud” which today we think of as being ephemeral, comes from the Old English “clúd” meaning “a mass of rock or a hill.” These old meanings restore the heft and materiality of data and cloud computing, making the objecthood of data irreducible. In a performance, “Data’s Entry,” a dancer will interact with this mound of keys, using the entire body to labor at this interface.
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