So I’ve been wracking my brain for the past five-odd months, trying to figure out the moment when the world became ‘modern’—partially because I took a class on secularization, mostly because I need something to fill up those empty hours where a vibrant social life should be. Then came the moment of revelation. I was watching that excellent documentary The Fog of War, and in discussing  the countercultural response to the Vietnam war Robert McNamara used the phrase, ‘an issue of population control.’ And the thought popped into my head, “that is modernity right there. ‘Population control.’ All the hopes, dreams, fears, lives, loves of a generation—reduced to a matter of sociological stability. Statistical reductionism. Damn.”

Well, the point here is that statistics are now and have always been a problem for those of us in the humanities—we don’t like data, it seems too self-assured, too cocky, we distrust the smug arrogance of ‘this is the FINAL ANSWER,’ as well we might. And for centuries, this has been a right and proper division: the sciences presume to know everything with their ‘hard data’ and dogmatic materialism, the Humanities chuckle snidely to themselves  at their colleagues’ dogmatic slumbers. And never the twain shall meet. 

I guess nothing lasts forever, because now we’ve got DH coming along and throwing a monkey-wrench into the whole program. DH sees itself as a peacemaker, bridging the gap between those techie folks who can’t see the forest from the trees, and us humanities people, who have our heads stuck in the clouds on a good day. (Where my head is stuck on a bad day is not suitable for disclosure in polite conversation.) Franko Moretti represents one direction—make the humanities more empirical, an attitude whose risks keep me up at night. Joanna Drucker ‘s “Humanities Approaches to Graphical Display” represents the other direction—make empirical data, or at least the visualizations thereof, more Humanities-friendly: make it self-critical, over-determined, conscious of its own fallibility. She prefers the term capta to data, the opposition being between something ‘taken’ and ‘given,’ the former implying mediation—and I think she is right to do so. Knowing how much our culture loves the visual over the textual, I think it best to critique some of her suggestions for DH data visualizations, and extrapolate a criticism of her argument from there.

 

Instead of a neat and tidy bar graph to illustrate the number of books published in a certain year, Drucker and her graphic designer present us with the following:

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Two immediate reactions: 1)Wow! Quantifying trends in publication is more complicated than I thought! 2)Where’s the Motrin?

It’s like–ever have one of those moments where you see someone doing something dumb and think, “I know what you’re trying to do, and I agree in principle, but—no. Here, now, in this way: just—no.” This is one of those moments for me. I think Drucker’s preference for capta over data is admirable—my God, crack open any newspaper with the slightest political bent and you’ll find biased belief supported by biased data over and over again—data is always subjectivized, and this is way too frequently forgotten. That is what Drucker is illustrating here, and I agree, and I get it. But it’s like reading Deleuze and Guattari’s rhizoic writing style, or referring to the feminine gender as ‘womyn’—you make your point so hard you beat your audience over the head, at which point they decide, “#$%& this intellectual stuff, what’s on my Netflix queue?’ 

What I mean is, this graph is confusing, but that is not the issue: it comes across as confusing for the sake of being confusing. I don’t feel like the bizarre notations and annotations are there to increase my knowledge of the data—I feel like the author is compelled to make a point about over-determination because I’m too dense to get it otherwise. I worry the typical viewer is going to find this annoying at best and patently patronizing at worst. So what would I do differently? Well, I think the polarity of clear/simple versus obscure/complex can’t be resolved through pen and paper means—we have to go digital. We need an infovis that can dynamically update itself based on user-input, but in such a way that the user is forced to exclude certain variables in order to include others. Suppose you first saw a standard bar graph, but each bar was an animated .gif showing different colors, varying heights and positions, etc. Then you would be presented with a pop-up menu by clicking on the bar and choosing your own variable, or combination of variables. The graphic could be as simple or complex as you want it to be—yet at each stage, by having to make a decision, you would be reminded (in a non-patronizing way) that there is no data, only capta. My $0.02, anyway.

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The intention here is to measure the affective mood on certain days, and the methodology is to have ‘day’ as an empty metrical placeholder defined by whatever it contains. This is a wonderful idea, and an innovative approach to metrical units—my only concern is that the initial intention, the measuring of affect, seeming to have been left behind at some point during the journey.

So here’s my suggestion: represent each mood as a different color. So on Sunday, let’s say eating and drinking are colored blue for relaxing, design is orange for intense work, and study is grey for boring work. An algorithm could then compute the dominant mood for the day, based on the number of times that mood appears, and how large the word in which does appear is sized in comparison with other words. Then you could have the whole day turn one color, or better yet, dilute or mix the color depending on the multiple moods represented. Maybe you could color the text, so the result might be something like Monday.

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Drucker concludes her article with the above graphic, envisioned as a response to this famous chart

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where individual persons are represented as mere dots. 

Again, love the intention, don’t like the implementation. Problem: I don’t see what this adds; I feel like the people look so fake that the effect is almost worse, because it tries to adds verisimilitude and fails—it reminds me of that moment in Fight Club where it is suggested that the illustrated persons in in-flight safety manuals must be high on oxygen in order to look as fake and vanilla as they do. So am I just going to complain? Well, here’s an idea, maybe its worse, idk. Keep the original format—have a dot representing an individual or individual family or whatever, but make the dot a link. Clicking the link opens up a pop up, where an algorithm generates statistical data for the ‘person’ at that location: physical description, median income, eye color, telephone number, preference for David Lee Roth or Sammy Hagar. Hopefully this will make those dots seem more personable—maybe not, for if the preoccupation with statistics is the problem, then defining a human life by artificially numbers might be the last thing we need. Then again, it might reinforce the point that personhood is increasingly dominated by demographics, marketing research, arithmetic calculations and the like in our day and age. 

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There’s not much for me to say here except—they’re marvelous! The aim in the former is to read an event not as disparate occurrence, but rather as a kind of vacuole around which the surrounding context is curved or inflected, the latter to demonstrate how travel time is derivative of the mood of the traveler. The subjective, personalized and over-determined aspects of the data are emphasized—but in such a way as I feel the emphasis is productive, rather than merely illustrative of the capta caveat.

 

Okay, so I’ve tried to give my opinion on what works and what doesn’t. So what? What is the relevance for the Humanities, specifically English Literary Humanities? Well I think the confusion between capta and data is alive and well in our own back yard. There is a long running trend in the English literary discipline towards a kind of fetishicization of the text, an adulation of the craftsmanship of the well wrought urn, an unfailing belief in the sacridity of the script. On one level this is right and proper, and none of us would be here if we didn’t cherish and admirer the beauty of literature.

But

a text is more than merely words and sentences and images; it is a network ruled by a certain tacit frameworks that govern the relationality of words, or concepts, or images, or affective responses. The text isn’t one thing, self-contained and beautiful and seamless; it is a patch-work of varying resonances and cadences, all vying for supremacy.

It has been difficult to quantity these with traditional approaches, partially because a vocabulary to describe them had not come to the fore—one had a specialized toolkit with which to diagram sentences and classify rhythm, but the conceptual apparatus has remained either obscured or mired in theory-speak. I think the sort of infovis Drucker proposes offers a new avenue for textual analysis, analysis which is radically self-aware, non-linear, and interactive. The key is proper visualization: there are interactive, dynamic possibilities within the visual domain that are simply not possible within the analogue medium. This should and, I am confident, will be explored in the coming years, as DH passes from early childhood to adolescence it will be well to bear Drucker’s suggestions and methodologies towards data in mind.

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