the semantic side of visualization

When I started thinking about how to analyze the design of information visualization, and the ways in which it could be made more "layperson-centric," my initial inclination was to focus exclusively on its visual syntax as something completely separate from its semantic content. In terms of programming design patterns, this would be the Model-View-Controller approach, where the visualization itself represents the "view" and "controller," and its construction ignores the internal details of the "model" (or, in this case, the data or information being visualized). I think there are a number of valid reasons to think in these terms (one obvious one being that "make visualizations about more interesting data" is not a particularly effective visualization design suggestion), but I've also come to realize two things: One, that visual design decisions can be greatly informed by the semantic content they address. Two, that visualization effectiveness in general can be enhanced by "extra-visual" considerations, such as the context in which they are delivered. A fairly trivial example of the first would be the use of maps to relate census data; the visuals produced by WorldMapper.org carry an impact and effectiveness that would not necessarily come through in a graph or chart representation. The following are a couple of examples of the second that I have been thinking about recently.

Last week, the MIT Communications Forum (hosted by the Comparative Media Studies department) held its first event of the Fall, a forum entitled "What is Civic Media?" (podcast available here). As a sort of launch-party for the new MIT Center for Future Civic Media (a collaboration between CMS and the Media Lab), the forum addressed the new possibilities for civic engagement and "participatory democracy" afforded by the rise of "Web 2.0 related" media (blogs, *casts, virtual worlds, etc.). To my pleasant surprise, information visualization was well represented as an important tool for promoting these practices! One of the panelists, Ethan Zuckerman of Harvard's Berkman Center for Internet and Society, presented several map-based projects designed to visualize media attention across the globe. Beth Noveck of NYU Law School explicitly stated the need for effective visualization of civic data to engage and inform participant citizens. I couldn't agree more!

She mentioned several existing tools out there, including the sense.us project (more on this in a minute), but I was most intrigued by her reference to smartvote.ch, a site that has evidently been deployed in Switzerland for several years now. In their words:

smartvote is a scientifically conceived online election aid for communal, cantonal and national elections in Switzerland.

smartvote aims to:

• improve the transparency of elections and give voters a new way to make an
  informed choice


• increase people's interest in politics


• demonstrate the potential of e-democracy and e-voting

The political profiles of candidates are established through questions about
their policies and attitudes, and these are saved in a database. Voters can
then answer the same questions, and smartvote will recommend to them those candidates who show the closest political match.

(Please excuse any messy formatting -- I've about had it with Blogger's post editor!)

The site has a strong visual component, where candidate's positions on various issues (gleaned from a questionnaire) are presented in several graphical formats, including a spider chart that creates a representation of their political "footprint." What makes it more compelling, though, is that a user can fill out the questionnaire as well, and see how their spider chart compares with those of the various candidates. This may be a trivial observation, but this sort of interactivity (at the "extra-visual" level) undoubtedly makes the system more engaging. Essentially they are offering the user the ability to insert themselves in to the data being visualized; we can easily imagine that a user would be more compelled to explicitly match candidate "footprints" to their own rather than simply browsing the footprints with only an abstract idea of what they are looking for. A huge part of engaging a user in a visualization tool (or any tool, for that matter) is getting them invested in what they are looking at; what better way than allowing them to see themselves in the data (incidentally, this may have been the sort of entry-point that made the Baby Name Voyager so popular)? The smartvote.ch site has only limited English translation, so I'd be curious to find out how it is being used and received by its audience.

The second visualization project using extra-visual techniques to great effect is the aforementioned sense.us and, more recently, Many Eyes. Developed by the folks at the IBM Visual Communications Lab, including Fernanda Viegas and Martin Wattenberg, both of these tools emphasize "the social side of visualization." In sense.us (which doesn't appear to have a live demo anymore), users can explore a series of visualizations of United States census data. While the visuals themselves are quite nice and clear, the key feature of the tool is the way that it encourages collaborative analysis, "recasting visualizations as not just analytic tools, but social spaces." Among other features, sense.us embeds comment boards within the visualization, allowing users to comment on, and mark up, particular features of the graphs (including the ability to "hyperlink" to specific views of the data, so that other users can see exactly what you have discovered through your manipulation of filters, etc.). This is all designed, obviously, to encourage discussion of the data -- another great way to engage and invest users. (Martin and Fernanda gave a great presentation on Many Eyes last Spring at the CMS graduate colloquium. For some reason the podcast of the talk was never posted, but I'm working on rectifying this and will post a link to it in the near future.)

This feature set continues in Many Eyes, which is a live service that allows users to upload their own data sets and create visualizations of them based on a series of graph and chart templates provided by the site. Once again, the graphics are quite nice (and all fully interactive), but the real draw is the "extra-visual" social element that encourages discussion and collaboration. I see it as a way of subverting the sorts of purely visual issues that come up when designing information visualization tools (some of which I have written about here already); essentially, it recognizes that a universally readable visual syntax may be impossible to produce, and simply uses this social framework as a "helper." Aside from more analytical discussion, a user confused or intimidated by the data has the ability to voice that confusion and learn from other users.

The value of this kind of interaction shouldn't be overlooked - I saw this while designing educational visualizations. Visualization can be imposing and confusing; many times it presents itself as a stand-alone, fully functional tool that dispenses information and expects to be understood without much qualification. It's very easy for users to become discouraged in this situation if they can't immediately "read" what is being presented (Donald Norman talks about this in "The Design of Everyday Things"), which is exactly the opposite of the experience someone should have with information visualization. Incorporating this social framework, I think, goes a long way towards easing this tension. If nothing else, it reminds users that visualization is for the people.

The final project I've been interested in along these lines is the work Hans Rosling has done at gapminder.org. Rosling has been using the Trendalyzer software to develop interactive, animated tools that "visualize human development." I first discovered him through his two great TED talks ("New insights on poverty and life around the world," and "Debunking third-world myths with the best stats you've ever seen"), which were extremely entertaining (for me, at least!). However, while the software itself seems well designed, what makes his presentations so compelling is the narrative that he builds around the software and the data it is presenting. Rosling acts as a sports announcer, giving a running commentary on the graphics as they move across the screen, and not only is his excitement for the data contagious, but it clearly increases the effectiveness of the visualizations (evidently so much so that the new "gapcasts" at gapminder.org feature Rosling green-screened over the Trendalyzer images, continuing to narrate the action!).

So, what does this mean in terms of visualization design? In this case it isn't totally clear to me yet. Obviously, information visualization should be a narrative, and Rosling has expertly produced examples of this. But how might designers incorporate some of the "magic" that Rosling generates in these presentations without the services of a charismatic Swedish sword-swallower (watch the first TED talk all the way to the end!)? In principle it should be possible, as he isn't cheating too much; most of the information he references in his narration is contained within the visualization he is presenting. So is it just his charismatic performance that adds value here? Certainly that's part of it, but ultimately what he's doing is serving as a guide, providing a guided tour of the data. In this sense, he's doing something that could conceivably be implemented in other ways, which might mean providing context for the visualization, or "tutorials" for its functionality, or finding other ways of increasing its narrative qualities. Or perhaps this overlaps with the sort of social activity used in Many Eyes. Or maybe information visualization does need more Swedish sword-swallowers.

In any case, what these examples indicate to me is that visualization tools are more than just visuals. While pure visual design works in many cases, addressing semantic and "extra-visual" content, directly or indirectly, can also encourage interaction and investment.