I thought I was in data-geek heaven when Swivel went live a few weeks back, but now there's a new suitor for my online-data-visualization affections: Many Eyes, a project of IBM's Visual Communication Lab. According to their (very eloquent) FAQ:

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.

Hear, hear! And the best part is that they back up all that eloquence with an equally powerful and downright elegant site. Unlike Swivel, Many Eyes doesn't let you overlap and compare different data sources, but it makes up for it by providing a whopping 13 different visualization styles, each offering an abundance of ways to sort, compare, zoom in on, and highlight data. On my first visit, I was taken aback by the heavy reliance on earth tones, but then I happened to flip past "the best statistical graphic ever drawn" in a copy of Tufte, and I think now I understand where they're coming from.

You need to do a little spreadsheet-shuffling in order to take advantage of the more complex visualization styles, but the site provides very clear instructions for this... and the results are gorgeous.

For my first experiment, I uploaded some data from a new table that our own M.L. Liu created for the 2007 World Almanac and Book of Facts, showing the slave and "free colored" (an official census designation of the time) populations of U.S. states and territories in selected decennial censuses. A few mouse-clicks later, I was looking at a perfect map of the US, color-coded to show relative population sizes for each selected census year; click on the box at right to explore the maps yourself, or even click back to the original data sheet to generate your own visualizations.

Done something cool with this data (or other data from the World Almanac)? Toss a link into the comments, so we can check it out.

Link: Many Eyes (IBM Visual Communication Lab)
Previously: Swivel It (Just a Little Bit)