An Inspection/Response to Empyre’s Conversations

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:

http://lists.artdesign.unsw.edu.au/pipermail/empyre/2016-July/009180.html

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:

http://lists.artdesign.unsw.edu.au/pipermail/empyre/2016-July/009205.html

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.

 

Stefan

 

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One thought on “An Inspection/Response to Empyre’s Conversations

  1. Stefan, you picked some awesome articles! It was really fascinating to read three articles and to hear three different points of view on raw data and data visualization.

    In Christina Mcphee’s post, “data visualization, equity and justice concerns around distribution and products,” she discusses the idea of teaching “data literacy” in order to counteract the imbalances of data access. Because raw data, like that found in records of civilian deaths, geospatial renderings of military actions, or fiscal year budgets for war, are often difficult for journalists, artists, educators, and policymakers to understand, the power of the data now lay in the hands of institutions and corporations. Data increasingly means power, and whomever has the data has control, both conceptually and physically. However, as a Kanarinka describes in the bottom of the post, beyond access to data, a means to analyze and make-meaning out of raw data is also necessary to counteract imbalances in data collection.

    This reminded me of current projects attempting to visualize the impacts of sea level rise in the Santa Barbara area. Although raw data is essential, being able to conceptualize data points can be even more important in wielding power. In Santa Barbara, Bruce Caron helped lightblueline.org, and other local activists to create a physical manifestation of data on sea level rise. They proposed to paint the 4-6 meters of projected sea level rise due to anthropogenic climate change on Santa Barbara streets and sidewalks, to mark the “vulnerability the community faces.” By visualizing raw data points in this way, lightblueline.org provides the general public with a means to make-meaning out of data on climate change. They hope this new knowledge will help the public better understand the significance of climate change, pushing them into action. But what if it does the opposite? Although mapping sea level change in this way will open up access to sea level data for journalists, artists, educators, and policymakers, what about the general public? Stepping over blue lines around downtown Santa Barbara, which serve to demarcate what will be underwater due to climate change, can be an overwhelming and traumatizing experience for the general public.

    In Katherine Behar’s post, she argues that all forms of data visualization are “generative,” in the sense that they are productive manifestations of data. She feels this can have the opposite effect in the fight to counteract the imbalances of data access. Erin McElroy, in “On the limits and hopes of mapping gentrification,” agrees to some extent saying, “something new coalesces through the visualization itself.” However, McElroy sees this generative process as beneficial in its ability to provide new “fodder” for thought on counter-cartography. In contrast, Behar believes that in data visualization, data is turned into an excess of information, overwhelming the viewer once again by its participation “in the dominant logic of overproduction.” I agree with both Behar and McElroy; in our media saturated world, data and data visualizations have the power to overwhelm and demobilize, so the ways in which we express data through visualizations is just as important as the data itself in developing “literacy.”

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