apophenic pretentia
Quick post from Michael Surtees has a nice line:
Unfortunately a lot that passes for data visualization isn’t much more than data fire works. It makes an impressive pop but fades into darkness. Entertaining but not really informative.
and some good links to other, true, data viz stuff.
Posting two vids, the first of an IxD talk in London using stop-motion animation to explain wireframes, the second of balsamiq’s demo of its paper meets dreamweaver tool. The first one, the stop-motion, is supposed to be faster than digital wireframing (in Visio, Illustrator, InDesign, etc.). It looks cool, has some personality, but it seems that chopping up bits of paper, setting them on other bits of paper, shooting the moments with a camera and then putting it in a movie, takes a lot more time than a well-designed, quickly executed digital frame. Anyway, it’s cool to see iMovie used in conjunction with other tools.
UX London redux video: Jane Austin & Chris Neale on sketching from Martin Belam on Vimeo.
And balsamiq, which doesn’t embed:
Just re-read Martin Neuimeier’s A Designful Company along with a bunch of my co-workers. Reading a book at the same time as other people is a fantastic thing to do — it sets of neuronic chain reactions and builds common language — and the book itself was pretty good. However, it highlights one of the things that continues to bother me about our collective obsession with innovation.
Neumeier has a passage where he describes his “good/different” chart. It’s not rendered as a quad graph in the Kindle version of the book, but given that it involves two variables with 2 possible values, it practically screams for one:
Like any good quad graph, “up and to the right” is the sweet spot, or, as Neumeier put it “as you might have guessed, ‘good and different’ is the combination that produces home runs.” This bugs me. While I know marketing is all about the whitespace, the onlyness, the thing that no one else does, it seems like a distraction from the real issue: quality and betterness. Good and different could translate into Netflix and the Prius (examples Neumeier cites). But it could also translate into another rev of Microsoft Word that has yet another feature which not only doesn’t make it better, it actually makes it marginally worse because of the clutter and confusion. This would still be “good but different” (making it worse didn’t make it bad).
“Good but different”, as a construct misprioritizes and muddies people’s thinking. Good can very easily become good enough (the Microsoft example) and can cause people to rush to novelty or newness as the goal. Rather than focusing on being better/best, we pick the most obvious and lowest possible standard (who would actually argue on behalf of not good?).
Netflix is much better understood not as different (they used the mail), but as better than the current space. Yes, they used mail, but they did so in order to address the flaws of the video store model: availability of films, locational convenience, and perhaps most important, late fees. Prius is still actually a car, but it’s a better car, not a different one: it burns fuels more efficiently, it runs quieter. The point wasn’t to be as good as the past, with a difference, the goal was to solve problems with fossial fuels and internal combustion engines.
We should really throw out the notion of being different and focus on being good, better, then best. Not only does it avoid the rush to novelty, but it forces product creators (marketers, designers, engineers) to get customer- and user-centric in their thinking. It forces us to step back and ask first questions: what is good/ what would be better? is our belief that the status quo is good really accurate? is our understanding of the category (video distribution) correct?
Scott Berkun has a great post about why we should stop saying innovation, with the great line, which to me says it all: “Just be good. That’s hard enough. Most things made in the world suck. They really do.” This is a big cultural change for most places because an understanding of quality, of what is actually good is usually missing (or not shared or driven by individual tastes) and a conversation to understand what’s good requires time. Much easier to assume that what’s in front of you is plenty good and look for something that makes it stand out. But that’s the real lesson of the above examples, a focus on doing something better, on solving the pain points.
Stop talking about innovation, stop looking for points of differentiation, build a better ________ and people will beat the proverbial cliche to your hackneyed portal and you’ll be all win-win in the sweet spot of whatever quad graph you have.
The first 1:30 of the documentary Moog has a great line from Robert Moog, the inventor of the synthesizer and one of the parents of electronic music: “I can feel what’s going on inside of a piece of electronic equipment.” There are other passages in the movie (which has great tributes from electronic music performers such as Sun Ra, DJ Spooky, Mix Master Mike, Electric Skychurch and a wonderful animated title sequence), where he shows how visualizes the interactions of circuits and components. Interestingly, he also points out that his synthesizers are analog instruments, not digital ones and that he knows musicians approach the physicality of the electrical vibrations in the same way they approach violin, guitar, and piano strings.
Anyway, that close connection to material — which strikes me as a result of closely working and experimenting with them — as a source of inspiration, quality, and innovation is a theme near and dear to me. So, I clipped the movie and encourage would-be innovators and inventors to check it out. Moog the man is charming, engaged, lives a full life, and could be a more earth-bound person to learn from than Steve Jobs, Edison, and other lofty luminaries.
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PS One last reason to watch the movie is a Schaeffer beer commercial in which a 70s-mustachioed dude in polyester, riffs on the Moog for 20 seconds before the jingle (“Schaeffer is the one beer to have when you’re having more than one.”) Worth the price of admission all by itself.
I like this video (found via Flowing Data) quite a bit, especially the reminder about the fragility of the atmosphere and curve of the horizon line. But is this data visualization or is it fact marketing? Data visualization should take data points and reveal patterns unseeable (or hard to see), or coax a story out of a perceived bunch of noise.
Vizworld just posted an interview with Edward Tufte which is a nice reminder of first principles of data visualization:
Not much has changed since Tufte began offering the Presenting Data And Information lecture years ago, other than a fourth book and a couple of new examples, but not much has to change when the point is returning to the first principles of information design: make wise comparisons, show causality, employ multiple variables and, above all, focus on the content. This point was driven home for me early on in the lecture as I internally formulated a question on one of my favorite topics: “How will the techniques presented in this lecture help me better represent 3d digital cities?” As if my mind had been read, the answer came: “Don’t ask how visualization techniques can help display data. Ask how data can be best represented.”
I like that it’s a statement of positive principles — show causality and comparisons, seek out complexity and richness, etc. — rather than the anti-prescriptions that are often associated with Tufte (avoid chartjunk, eschew Powerpoint).
Love this email I just got from Amazon:
Full disclosure: I get quite a kick out of the Dan Brown oeuvre, despite the horrible writing. It’s like the old computer adventure games made into a book. Literally. The old games — like MYST, Journeyman Project, Tex Murphy, Last Express, Obsidian, Lighthouse, Gabriel Knight, even the fighting adventure games like Resident Evil — had a winning formula:
- gruesome/startling crime in the beginning (Lighthouse wins this one hands down with not one but two great openings: 1) you explore a house with interesting objects, but only when you press the answering machine button to get a hysterical call for help does the game kick in with a great drive through the rain sequence that presents the credits and great animated lightning effects); and 2) when you explore the house of the friend who called you, you see a baby quietly sleeping in its crib. When you return to the baby’s room, you see an alien stealing the child. Seriously jump out of your skin freaky. Dan Brown has the usual Robert Langdon being interrupted in some refined pursuit (dreaming about hiking the pyramids with a babe, or giving a lecture) and then being dragged to a mutilated corpse.
- discovery of solvable riddles — adventure games are riddled with barely- to not even close to plausible riddles that you’re happy to solve. They propel the story. Nearly every image presented in Dan Brown allows the reader to puzzle out the clue.
- obscure reasons for villainy The worst example of this was a ten minute or longer discource in Journeyman Project Turbo. These reasons usually warrant a page or two of monologue and sufficiently flawed logic for Langdon to feel the need to correct the villain on the true meaning of the text. Not quite “that belongs in a museum” but close.
Final disclosure, while I won’t leave my battery on, my morning ritual of turning on the wireless will have an extra jolt of excitement (I like it even when I’m just getting the paper) tomorrow morning.
Ben Fry, creator of Processing (or Proce55ing for those that remember) and data viz guru at MIT, has an absolutely fascinating visualization of how Darwin changed the text of “The Evolution of Species” in the thirteen years following its publication.
The labels across the top are chapter numbers, the dashes underneath represent text from the book which you can see on mouse-over. The color bars indicate the different editions.
I called it fascinating on first look, but should probably be more measured or specific. I hate when we fail to distinguish between fact illustration (making a single thing visual) and data visualization (revealing previously unseen stories through a rich visual worth looking at several times). This falls somewhere in between. The final state of the chart, after the 6th, and lengthiest, revision does tell a story:
The most obvious part of the narrative is the addition of an entire section and extensive revisions to the final section in the 6th edition, indicating a structural bolstering of the argument and possibly responses to ten years of critique. The speckle patterns, small bits of color, show a lot of tinkering/revising in the first three editions. These all support Fry’s introductory point:
We often think of scientific ideas, such as Darwin’s theory of evolution, as fixed notions that are accepted as finished. In fact, Darwin’s On the Origin of Species evolved over the course of several editions he wrote, edited, and updated during his lifetime
I’m wondering, though, whether this illustration tells the story better than the text?
What does make it fascinating overall is the ability to mouse over the sections (the small gray and colored stripes) and read the text underneath. Might be a better tool (if the stripes were a little bit bigger and easier to mouse over) than it is a data viz.
Two links today, one old, one new, highlighting how over-use, mis-use, mindless-use of the word has robbed of it meaning and impact:
From the presumably soon to be renamed “Innovate on Purpose”, a nice line about the cost of setting overstated goals: “By placing too much emphasis or spotlighting events that aren’t really innovation, we place a lot of good work at risk.” There’s another nice line that hits on the idea that innovation is a habit, “consider innovation as a repeatable, sustainable process rather than a quick brainstorm or two and one somewhat interesting product”
Scott Berkun is the author of the other, older post where he makes the ballsy statement: “Just be good. That’s hard enough.” Not only is it hard, it’s actually often innovative, better than what’s out there.