Graphicacy

Reading Time: 2 minutes

For the past few weeks, “graphicacy” has insinuated itself into the part of my brain where nagging curiosity comes from (the self-nagebellum), becoming the terministic equal of an ear worm: word worm. Term worm? Lexical maggot? Whatever. And there, for weeks now, it has wriggled, dug in.

I don’t recall encountering “graphicacy” before Liz Losh mentioned it casually in her presentation to EMU’s First-year Writing Program during her visit last month. I wrote down several things from Liz’s talk, but graphicacy was there on top of my notes, large and starred. It stands to reason that graphicacy keeps company with literacy. Both are –acy words, which means they are adjectives converted to nouns and that they name or identify conditions. Presumably these, too, are nominalizations, but they by-pass verbs, which is the problem I’ve been thinking about. We have reading and writing to verb literacy, but what verbs graphicacy?

I had to do a little bit of cursory sifting and searching for graphicacy, to start. It seems like the term was initiated in a mixed and sprawling range across math education (learning to plot points and interpret graphs), geography (facility with maps), and graphic design (technical-aesthetic savvy). Late last month, it surfaced in the context of a conversation about multimodal composition and the graphic rhetoric we have adopted at EMU, Understanding Rhetoric. This is the main reason it took hold for me: graphicacy seemed to gather an array of practices related both to understanding and making visuals. It sweeps into one pile an assortment of visual communications–graphs, maps, word clouds, comics, painting, photography, typography, data visualization–much in the same way visual rhetoric does. And yet, with graphicacy as with visual rhetoric, it feels like we are still missing a sufficiently encompassing verb to capture the array of practices.

At our Advanced WAC Institute on campus late last April (or was it by then early May?), I worked with a team of colleagues on a new (for us) configuration. With colleagues from Communications and Education, we put together an institute keyed on five complementary practices: writing, reading, critical (or I would say “rhetorical”) listening, speaking, and visualizing. The fifth term, visualizing, was mine to introduce to institute attendees, and it was the most difficult to identify with a verb that was adequate to account for the frame, which amounted to concept mapping, drawing/sketching as heuristic for arrangement, and creating occasions for students to work at the intersection of textual and overtly visual and designerly composition.

Because we called it “visualizing,” we began the sessions needing to backtrack and contextualize. With visualizing, we weren’t talking about conjuring brainbound images or about an indwelt priming of the mind’s eye to work on problems or particular ways of seeing. These were among the associations attendees made with visualizing. And this seemed reasonable. Visualizing wasn’t quite the right verb. But what is the right verb? What is the general verb comparable to writing, reading, listening, and speaking that relates not only to seeing but to creating visuals, especially in consideration of vector illustration programs and shape-based concept mapping software that bears only faint relation to drawing?

Graphicacy stirs this question yet again but does not quite answer it. But I hope not to call it “visualizing” ifwhen we convene the institute again next time.

Plotting Intensities

Reading Time: 2 minutes

I first caught word over at

Junk Charts
of
this infographical rendering
(in the

Sunday Times
) of a week of concert-going. The spread includes profound
thoughts, counts of the people on stage, quality arcs of each show, more
profound thoughts, entertaining phrases, profound guests on stage, and best
parts, all convoluted into charts, graphs, stacked bars, and bubbles. When
I first saw the quality arcs, I thought it would be cool to throw something like
that together to suggest rising and falling intensities over the course of a
graduate program of study. But heck, it took me four days to get around to
posting on these few pieces that churned through the aggregator on Sunday, so
it’ll be a few more days before I get around to drawing up quality arcs of my
own.

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Clouds, Graphs, Maps

Reading Time: < 1 minute

A couple of days ago Mike posted notes on
my

CCCC talk
from late last month, and I was reminded that I’m at least ten days
past due on the video
I said I would
produce
following the conference.

I recorded the talk to an mp3 yesterday afternoon and went to
campus last night where I planned to use iMovie to sync the audio with jpegs of
the slides. Because the slideshow includes text, I needed to get the
resolution right, but, well, it started to get late. I started to get impatient.
I was able to output a reasonably readable mp4 file, but for whatever reason, I couldn’t get
Google Video or
Daily Motion to encode it.
Finally Jumpcut accepted the file, so it’s
available below the fold (even if much of it suffers from jaggies). The original mp4 is available for download
here.

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Visual Findability

Reading Time: < 1 minute


Find It! (via)
is a simple game of noticing or failing to notice a shifting visual scrap. Try
it out; you’ll see (or not). The screen’s general field is occupied by a
"static" image while some minor, hard-to-find, detail gradually changes,
materializing in the phosphor of the screen or fading slowly from view.
Trickery! The picture’s motion is segmented and minimized: quieted to a soft,
slow wink. Because the variation is slight, the unseen or missed in
the timed glance is amplified, exaggerating the sense of visual richness of the
mundane digital photograph. What did I miss? What can’t I see all at once?
How many pixels-amuck escape my peripheral field in a 600×400 spread?

The Networked Image

Reading Time: 2 minutes

I first picked up on
Google’s Image Labeler
two days ago (via).
In a nutshell, Image Labeler addresses a semiotic problem: the indexing of
hundreds of thousands of images based on semantic assignments in the visual
field of each image. Indexing an image depends upon the assignment of
keywords that correspond to the objects represented. Google Image Labeler
makes this process into a game of peer review: in this two person game, a player
win points by registering a descriptor that also appears on the other person’s
list.

Tracing

a

few
links (succumbing,
that is, to the beckoning of a surprising curiosity), I briefly started to follow the life
of this conversation in computer science and art. Most intriguing in this
regard was the talk embedded below, a talk called “Human Computation” given by Luis von Ahn at Carnegie
Mellon.

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