interpreting visualization :: visualizing interpretation

interpreting visualization :: visualizing interpretation

In the second chapter of Graphesis, Johanna Drucker takes her readers through the development of a variety of specific visualizations across time, from timekeeping in the Roman empire all the way through to complex mathematical visualizations with modern digital computing tools. Most crucial in her account of these visualizations and their uses for Drucker, however, is her explanation of the societal context in which they spawned - specifically with what assumptions and interpretations are baked in.

It is in this chapter, Drucker extensively lays out her skepticism and caution regarding the conflation of visualization and objective knowledge. She argues that all data are capta, which I interpret as observations or interpretations of one's surroundings rather than hard pieces of fact, and all information is interpretation. She emphasizes this point in this critical chapter, retorting:

...the rendering of statistical information into graphical form gives it a simplicity and legibility that hides every aspect of the original interpretative framework on which the statistical data were constructed (128)

Her standpoint is morally sound and well backed by examples of misuse - most interestingly to me in her comparison of network diagrams/topic maps to tree diagrams. While order and spacing carry analytic value in tree diagrams (you cannot adjust the spacing or hierarchy without changing the meaning), while variability in the configuration of network diagrams may not signify a substantially different relationship between the data points represented. Readers may easily still interpret aspects of this configuration as having semantic value (e.g. spatial differences), potentially even without realizing it, creating a very real window for misinformation.

I find Drucker's case for caution in conflating visualization as fact very compelling, and I am curious to what extent she sees analytical and intellectual merit for the use of visualization in fields outside of humanism, if she sees any at all. Her passionate mistrust of visualization is well documented in this section with flowery language (which I found overly obtuse and dense at times):

These graphical tools are a kind of intellectual Trojan horse, a vehicle through which assumptions about what constitutes information swarm with potent force (125)

She mentions that "crudely conceived numeric statistics are useful only in the most reductive circumstances," (133) but I find it hard to believe that fields like Mathematics and Science do not benefit from the use of data visualization that drive these disciplines towards the discovery and communication of universal truths that hold real intellectual and societal merit. Drucker herself cites Snow's visualization that helped identify the origin of Cholera outbreak, which saved many lives. Her additions add unmistakably important societal context about who Snow's data points are and how they feel as human beings, but I am curious to hear the class's opinion on how these additions that make this a "more complex statistical view" influences its effectiveness and/or importance within society.