You know that commercial for the used car website where a savvy buyer summons a matrix of millions of cars out of nowhere with a few clicks of her mouse? As she scrolls through models, styles, and color preferences, legions of shiny cars slide past her desk at hyper, cartoonish speeds as if on a gigantic conveyor belt, but she doesn’t flinch. Not a single hair is blown out of place.  It’s all virtual! As she proceeds through her selection of options, getting more specific with each click, the raft of cars is likewise reduced: from all of a style, to all of a model, to all of a color, until finally she’s left with the single, presumably perfect, one.

What makes this commercial effective is how it makes visible the buyer’s selection process. Every buyer follows a hierarchy of choices, a forking path that ultimately leads to the final result. By literally showing us lines of cars receding into infinity along every axis, the commercial reminds us how mind-bogglingly vast are our options. And makes the case for the website as a tool that allows us to wield a kind of magical, playful power over them. With each whimsical click, we command those legions of cars to dance. 

If you’re looking for another stunning example of visualization as a playful, interactive approach to communicating and conceptualizing complex data, look no further than the NameVoyager. Based on US Social Security Administration name records going back to the 1880s, the tool offers an interactive visualization of name trends that starts with a general "sea" of names but lets you quickly dive in to more specificity. It simply and beautifully organizes and represents information in a way that’s searchable, browseable, and perfectly contextual.

So who’s behind this miraculous baby-name machine? As it turns out, someone with serious wonk cred: Martin Wattenberg of IBM’s Visual Communication Lab. His work in information visualization bridges the worlds of data analysis and expressive art. More of Martin’s professional and artistic work here, here, and here.

George Siemens has also been thinking about visualization lately:

Lately, I’ve been somewhat absorbed by the value of data visualization.
In recent presentations, I’ve described technology as performing a
"grunt cognition" role in our efforts to make sense of complex and
changing information landscapes. Consider a flickr tag cloud.
The tag cloud is a visualization of the aggregated activities of many
flickr users. Visualization, performed by technology, does the grunt
work of creating patterns which we are then able to analyze, allowing
us to move more quickly to meaning making. Visualization will play an
increasingly central role in helping us to cope with information
growth. A picture is worth more than a thousand words – it’s worth a
thousand data sets and tags.

Continuing, George writes about Martin Wattenberg and a new Visual Communication Lab project called Many Eyes. Its raison d’etre is to move information visualizing beyond data analysis to socially-mediated meaning-making.

All of us in CUE‘s  Visual Communication Lab
are passionate about the potential of data visualization to spark
insight. It is that magical moment we live for: an unwieldy, unyielding
data set is transformed into an image on the screen, and suddenly the
user can perceive an unexpected pattern. As visualization designers we
have witnessed and experienced many of those wondrous sparks. But in
recent years, we have become acutely aware that the visualizations and
the sparks they generate, take on new value in a social setting.
Visualization is a catalyst for discussion and collective insight about
data. . . .

We believe that visualizations gain power when
multiple people use them to communicate, and that communication gains
power when multiple people can visualize and explore information
together. We want to democratize visualization, enabling anyone on the
internet to publish powerful interactive visualizations and start their
own data conversations.

This feels new: moving beyond data as presentation to data as seed of conversation.  George’s post includes a brief interview with Martin Wattenberg about Many Eyes, and how it extends the typical notion of information visualization from straight analysis to using the data for whatever purposes are near and dear to someone’s heart: art, politics, activism, baby names, etc.

It’s also about the rhetoric of data. I’m not sure how well persuasion
happens through audio or text. Persuasion by data-graphics can make an
impact. We are giving people a tool to bring computational power of
bringing visualization to the people.
We want to get to connective analysis – be smarter about these things,
persuade. A discovery that doesn’t get known is one that doesn’t get
communicated or understood. Rhetoric, persuasion, and communication are
so important.

I agree. . . and I’m tempted to go out on a limb and propose a further extension. The value of something like Many Eyes goes beyond its more-eye-catching-than-thou persuasiveness, its stunning appeal. It even goes beyond the communicative aspect Martin describes. Clear, powerful rhetoric is valuable and relatively rare, but it isn’t entirely the point. Where Many Eyes really stands apart is through its interactivity, transparency, and intentional design for collaboration. Once it’s about swapping ideas and datasets, once the conversation is on, visualizations become part of a social context, and it’s a short step from static visual showpieces to living relationship models.

I couldn’t resist experimenting with Many Eyes last night—see the poor orphan samples of my labwork below. It’s incredibly easy: setting up a user account takes a couple of minutes, and the "upload data" page is virtually foolproof. Visualization options include various traditional graph styles, beautiful less-familiar forms like bubble charts, plus a tag cloud for straight text.   

Minnesota Department of Education 2006-07 Special Populations – bubble chart

Dr. Martin Luther King, Jr. "I Have A Dream" speech – tag cloud

Remix of January 2007 Top Edubloggers data gratefully borrowed from Scott McLeod. [Scott, if you still plan to revisit this data and post an April update, I’d love to see what kind of spin you could give it with Many Eyes.]

What does all this mean for teaching and learning? Not sure yet; I have a lot of learning to do. If learning in the 21st century is about
collaboration, I think Many Eyes provides a rich opportunity to
conceptualize and understand ours and our students’ collaborative relationships in new
ways. And visualization may be just the beginning.  Should we
anticipate development of tools that use other sensory filters to explore and express
complex concepts? Auralizations? Tactilizations? We may be witnessing the genesis of whole new world of sensory terminology and concepts to describe relationships, organizations, structures, and communities.