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A blog about security, privacy, algorithms, and email in the enterprise. 

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Seeing Words: Communication in the Age of Abstraction

mayan symbols

mayan symbols

Will the rise of image-based applications birth the next dominant form of communication? 

As you might not find surprising, I’m e’re alert for innovations in email. Yesterday, I came across a cool new service called PhilterIt, which filters and symbolizes email from brands and priority accounts. Users drag an email from a brand to their brands dashboard, creating a filter that will house all incoming email from that brand. The filter is represented by the brand's logo, and unread emails are presented by a numeric badge.

PhilterIt’s value seems to be around organizing and giving you quick insight into your daily deals email. Given the proliferation of these, it’s not a bad idea. As a prioritization service, it seems a bit less useful, because the sender photos provide no information on the emails’ contents. However, limited though PhilterIt’s audience may be, its core functionality is yet another stepping stone on the path to a completely symbol-based communication system.

The first communication system was nonverbal, the second, oral, the third, symbolic, the fourth, written. Now symbols are again becoming a mainstream form of communication, but this time, they are symbols based on words. The most widespread example of this is Google Image Search: give a word, get a picture. There's the reverse image search engine TinEye and similarity image search engine Retrievr. There’s Pinterest, which is geared more towards browsing and serendipitous discovery.  There are the purely or mostly visual e-tail and social sharing sites: Fab.com and The Fancy. There’s the animated gif craze (what should we call #makeitstop). There are visual-centric quick-blog platforms like Tumblr and Posterous. There is the personalized art recommendation engine Art.sy….

Then there is the rise in popularity of data journalism: stories about numbers must be accompanied by the numbers themselves, visualized in web applications like Tableau and Google’s Chart API and Fusion Tables. These do what information visualizations have always done: illustrate numbers—but now, the user can interact with the information, can click on specific sections and adjust ranges and, if desired, go behind the representation to the raw data itself.

bullseye

bullseye

The possible causes of this shift are myriad. Maybe it’s because we have more ways and less time to communicate, and so feel impelled to compress our messages as best we can. Maybe it’s because TV shows and films and records are no longer restricted to TV sets and theatres and stereos. Maybe it’s because our fingers are tired.  Whatever they are—and they may be all, or none, of the above—their effect is a sea change in how we create, deliver, and process information. Abstraction is the new contraction, or  , though personally, I’m reluctant to swap my signs, with their (relatively) easy dissectability for symbols, whose range of meanings are myriad and fluid.

What about you? Do you use any visual-centric communication platforms or services? Which ones?

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Edward Tufte on Presenting Data and Information

Will (our UX Engineer) and I went to painter/sculptor/data scientist/visualization pioneer Edward Tufte's course on "Presenting Data and Information" at MIT March 22nd. The first half of the day was largely about the related natures of being the presenter and the consumer of a presentation.

Thoughts on consuming a presentation

  • Digesting a graphic should take time.  Many graphics contain 1000s of data points and it is unreasonable to expect them to be understood with a cursory glance.  The analogy was something like:  "If the saying is that a picture is worth 1000 words, then why should there be an expectation that a graphic should be digested with any less care and effort than that required by those 1000 words?"
  • Be wary of conclusions that are too good to be true, especially if the author refuses to reveal his sources or methods.  Cherry-picking, even unintentionally, was brought up as a common problem.
  • However, resist questioning the motives of the presenter.   Human beings are notoriously bad at this, and it provides a way to dismiss the argument out of hand without dealing with its components.

Thoughts on creating a presentation

  • Just as consuming a presentation requires effort, so too does creating one.
  • Tufte's thesis appeared to be that the purpose of a graphic is to support analytical thinking.  Therefore the design goal for the graphic flows from the type of thinking that is to be supported.
    • If the thinking task is to understand causality, the task calls for the design principle:  Show causality.
    • If the thinking task is to answer a question and compare it with alternatives, the design principle is:   Show comparisons.
  • He then went into a more tactical discussion of some examples, with some rules of thumb.
    • Lines that link elements on a graphic should convey the nature of that connection.  You should never have generic linking lines.
    • Boxes in graphics are almost always superfluous, and are examples of "chart junk" which serves to add to the visual  noise of the graphic but not actually aid in the thinking task.  The items' relative positions on the graphic are almost always sufficient to show the aspect that the box is attempting to show (think of how maps don't have boxes around city names).
    • Display the important things (comparisons/causality) next to each other in space, not stacked in time.
    • If nothing else works, use small multiples
  • Conveying the presenter's credibility can be just as important as the contents of his presentation.
    • Acknowledge the sources of the data
    • Be especially careful of data that is too good to be true (the CERN loose cable debacle comes to mind)
    • The authors' proximity to the data.
    • The authors should put their names on this data and take ownership of it.
  • The presenter should not bring attention to the method used to do the analysis and generate the graphic.
    • Any discussion of the method means that the data itself isn't being discussed.
  • When trying to find examples or starting points, look at things that work in the wild for many different users. Think of the sports stats on espn.com, or maps, thousands of people look at them, all different kinds of users.
  • Do whatever it takes to get the information across, and help the user think and reason
    • Always try to minimize format figuring-out time and maximize content figuring-out time

Tufte's Presentation Script (his alternative to going through a slide deck)

  1. A high resolution data dump of the findings (data dump not in the sense of raw data, but rather that all (or at least as much as is feasible) of the contents should be viewable all at once.
    1. Stacked in space, rather than stacked in time like in a slide deck
    2. This is often a handout that is given to each of the participants
  2. Let everyone sit there and digest some of it. (but not too long)
    1. By having a high density document, each participant is simultaneously digesting the whole thing in aggregate, and digesting the individual bits that are most relevant to them. This prevents the condition where each person is waiting for the part of the presentation that relates to their domain.
  3. Go over your interpretation of the data, referring to the document.
  4. Lastly, for groups under 40 people, are there any questions?  then discuss.

 

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