Previously in this blog, on two separate occasions I commented on new web-based services—both available to the public—for exploring and sharing data visually: Swivel and Data360. I welcomed the worthwhile intention of both—to provide a public forum for sharing and discussing insights discovered in data—but I found the visualization capabilities of both rudimentary and in the case of Swivel especially, in some ways ineffectively designed. I believe in the inherent value of information and fully support efforts to make it available in ways that challenge people to think and hone their analytical skills. Upon discovering these fledgling services, I found myself longing for another—one that provided exceptionally well designed visualization tools, which could give this worthwhile venture a better platform for meaningful and eye-opening discoveries and collaboration. Knowing that work in this area was already being done by some of the brightest lights in the information visualization community at IBM Research’s Visual Communication Lab, I hoped that they would step into the breach. Yesterday, my hope was realized in the form of a new service called Many Eyes.
Here’s an excerpt from the site, which describes its objective:
Many Eyes is a bet on the power of human visual intelligence to find patterns. Our goal is to “democratize” visualization and to enable a new social kind of data analysis…
All of us at the 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 all deal with data that we’d like to understand better. It may be as straightforward as a sales spreadsheet or fantasy football stats chart, or as vague as a cluttered email inbox. But a remarkable amount of it has social meaning beyond our selves. When we share it and discuss it, we understand it in new ways.
The same beauty and passion with which the team at the Visual Communication Lab has expressed their intentions can be seen in the service that they provide, and especially in its visualization tools. Martin Wattenberg and Fernanda Viégas are the two members of this team whose work I already know and respect. I would expect nothing less from them than the fine collaborative visualization environment that they and their colleagues have created.
As a brand new site, still in its alpha phase, Many Eyes does not already offer everything one might desire when exploring and sharing information visually, but what they do offer is finely crafted, and it extends to a surprisingly large number of visualization types, considering that this is a first release. Even geo-spatial (geographical map based) and treemap displays are included. The charts are things of beauty that don’t resort to the superfluous decoration (3-D bars and pies, garish colors, silly lighting effects, etc.) that is common today in most commercial visualization tools.
Here’s a simple line graph that I created to compare U.S. consumption of apples and oranges (yes, I’m comparing apples and oranges) as it has changed from 1970 until 2003:
Notice how your eyes are drawn to the data and how easily you can follow and compare the ups and downs of apple and orange consumption across the years. This is the product of expert design. If you wish to see precise values without going back to the data set, just hover with the mouse over any point along a line and the value appears, but only when you want it, so it doesn’t clutter the graph when you don’t.
To give you an example of the more sophisticated visualizations that Many Eyes offers, here’s a treemap, which compares highway vs. city mileage of vehicles, organized by class and manufacturer:
I’ll resist the temptation to show more examples, because you’ll have a lot more fun if you go to the site and explore it directly.
Given their commitment to support data exploration as a social event, they have incorporated means for people to share their thoughts verbally as well, by people to post comments and questions in the collaborative spirit of discussion boards and wikis.
Many Eyes doesn’t already do everything you might find useful while exploring data and it certainly isn’t a replacement for robust commercial visual analysis software, but even as a free web service, it already gives you better visualization functionality than most business intelligence software products. In the few minutes that I’ve had so far to explore the site, I listed a few things that I would like to see added or improved, such as the ability to sort categorical items in a graph by value (for example, in a bar graph that shows the consumption of all fruits in 2003, sort the bars by the amount of consumption rather than alphabetically) and the ability to compare data distributions using a box plot. I sent my list to Martin Wattenberg and received a quick reply that both of these features are already on the list for a future release. (Keep in mind that the site was just released in its alpha state.) I suspect that Martin and his colleagues didn’t wait until everything they had planned to include was in the site before previewing it, because the earlier release of Swivel and Data360 made them anxious to show their hand as soon as possible.
The value and extraordinary power of information visualization for analysis is quickly gaining recognition. It’s an exciting field, which is far too often undermined by poorly designed visualizations, which is shown so vividly in most of the dashboards that vendors advertise. A finely crafted visualization service, such as Many Eyes, is a “site” for many sore eyes, thanks to the dedication and skill of the folks at IBM’s Visual Communication Lab.