The first article I looked further into was the following: http://lists.artdesign.unsw.edu.au/pipermail/empyre/2016-July/009159.html
In this reading, there were multiple points of interest that seemed unique in its approach in quantifying data. Essentially, both the inquirer and responder discuss the implications of hard data in uncommonly quantifiable aspects of events. In this case, there is an argument made that the ways that hard data is often constructed is often limited in its ability to reify in noticeably and categorically efficient ways. However, the responder claims that as Xenakis had previously tried to quantize and visualize music in his older works (as I have also become familiar with in my own studies in the UCSB music department), Luke Dubois’ Hard Data (2009) and turbulence.org have similarly made attempts in quantifying and visualizing data sets in a way that become physical and no longer conceptual. In fact, another example given of neighborly.com explains how it becomes possible to physically intervene into larger, hegemonic structures that are otherwise intangible. By doing so, we are constantly challenging the way in which concepts and events are visualized.
The second article I read was the following:
This reading was an introduction of Katherine Behar and her work. In this particular article, Behar addresses her own personal interests and her own positioning in data quantification and visualization. To further inspect her discussion, I will approach her comments on big data vs. self-obesity. In this case, she argues that both the ways in which big data are often visualized and the obesity of one are similar in that they become excessive modes of production. By creating these quantifications of data in the forms of maps, paintings, graphs, etc., we are denaturalizing the raw data and rather interjecting artificial interpretations of the canon. She further goes into her own work as she introduces “Data Cloud,” an art-piece composed of 6000 QWERTY keyboards. Ultimately, this piece would be a demonstration of the excessiveness in unquantifiable data reifications. In other words, Behar’s work underlines the artifice of the “cloud,” which is an illusion created by capitalists as an attempt to make networks feel economical and somewhat magical, when they in fact occupy physical spaces.
The last article I read was the following:
Despite the other two conversations discussing the theories and utilities of mapping data in physical media, Erin McElroy introduces her own implications of data visualization as a politically challenging and active form of data mapping. Of course, all authors on Empyre have created and discussed their own data visualizations; however, McElroy comments on the increasing, and sadly alarming, rates of gentrification in the Bay Area. In fact, McElroy’s website for AEMP shows a visualization of the Bay Area and the disturbing increase of red dots to signal an eviction over a timescale of 10 years. By doing so, she wishes to express her own discourse on gentrification via the Ellis Act in a way that could be understood as personal and corrupt. Through McElroy’s work on AEMP, we are better able to understand the density of gentrification through a visual perspective.