Since November 8th, you’ve been using the new Ruby on Rails version of Many Eyes! You may have used it already if you’ve used the New York Times’ Visualization Lab.

Doing a full rewrite of an application is not something to be taken lightly, but we’re confident that the move to Rails has been well worth it. It’s been a joy to develop, and the site is running faster than ever.

“Faster?” We can almost hear you say. “I heard Ruby was slow!”

While it’s true that Ruby isn’t the fastest executing language around, Ruby is faster in a few important ways. It’s taken less time and fewer lines of code to produce equivalent functionality in Ruby, and it’s been easier to optimize the application. In the end, this means our application actually runs faster.

Last but not least, there have been a few small changes to the site, such as the new dataset tag cloud and the ability to change your display name and profile under “my stuff.”

So what does this mean? It means that Many Eyes is now running on a system that is more flexible and easier to maintain, which will allow us to add new features more quickly. With that in mind, we would love to hear your feedback! What would you like to see on the site next?

Please feel free to jump right in – it should feel nice and zippy. We’re still working on making sure all the old links and embedded visualizations behave properly, so don’t be too concerned. We’ll have all of that working over the next day or so.

If you see anything unusual, feel free to contact us via the usual channels.

From Friday at 6pm EST until Saturday 3pm EST, Many Eyes will down for scheduled maintenance. We’re moving to a new server and doing some data migration. Sorry for any inconvenience this may cause, but we think you’ll enjoy the performance upgrade. It may be back up before then, so feel free to check back early.

We’ll have some more news coming soon, so stay tuned!

Photo credit: Flickr user jphilipg

We’re not quite ready to launch Wikified to the public yet, but we’d love to know what you think of it. If you’re interested, you can sign up for the closed beta and get a sneak peek at what we’ve got in store.

Wordle marks a departure from the more analytical visualizations on Many Eyes. Why bring a self-described “toy” to a site for social data analysis? People have reported finding value beyond entertainment in creating these word clouds. Teachers have used Wordles in classrooms as conversation catalysts; others have created them to express their identities, and scholars have used them to visualize the output of statistical explorations of texts.

And Wordle brings serious typographical considerations into a realm where usually the
biggest choice is “serif vs sans-serif.” Part of the appeal of Wordle lies in a number of clever layout and editing capabilities. First off, it breaks the grid of regular tag clouds by treating all white space available (both in-between words and even inside a single word) as fair game for layout. For instance, a small word could end up appearing inside the “O” of a bigger word. Second, it allows words to be written in any given direction: horizontal, vertical, and diagonal. Third, there are choices of fonts, layouts, and colors. And, if all this weren’t enough, it also allows the creator to remove any word she doesn’t want to have on the cloud (right-click a word and say “remove”). Pretty sweet!

So come play with Wordle! We hope this toy brings you some pleasure and, perhaps, some new insights.

Today we’re featuring two fun tutorials that explain how you can go from finding a data set on the web to uploading it to Many Eyes and creating your own visualizations:

1) The classic “FMUV” (Find, Massage, Upload, Visualize) tutorial by our colleague, Jonathan Feinberg.

2) The brand new “Northstar Nerd Tutorial: Data Visualization via IBM’s Many Eyes” by our user Richard Hoeg.

We are grateful to both of them for putting together such cool presentations–thanks for the help!!

If you happen to have your own tutorial, let us know. We’d love to feature more of these.

There’s no question that our users like visualizing the differences between related texts, but making comparisons by looking at one text a time is difficult. Today we’re launching a new version of our tag cloud, which we hope will allow for easier and clearer analyses.

If you want to compare two texts directly, you can merge them (see the instructions for details) and then see a special “interleaved” tag cloud, which will let you compare side by side the relative frequencies of the words in the two texts. You can see an example here:

which shows the US presidential State of the Union address from 2002 and 2003. The 2002 speech is in orange and the 2003 speech is in blue. You can see a number of differences directly: “Afghanistan” shrinks dramatically from 2002 to 2003, and “Saddam” seems to grow in proportion.

Give the new tag cloud a spin! We’re looking forward to seeing what comparisons our users draw next.

We are happy to announce that members of the VCL have two visualizations featured in Design and the Elastic Mind, the new exhibit at the MoMA in New York, which runs from February 24 to May 12, 2008.

History Flow, our visualization of Wikipedia editing history is making an appearance with “chocolate” and “abortion.” Thinking Machine, a visualization of the complex decisions that underlie strategic thinking, reveals the machine’s thought process as it tries to beat you in a game of chess.

The exhibit explores the relationship between science and design in the contemporary world. With over 200 pieces, it spans a variety of fields: from nanodevices to vehicle constructions, from appliances and interfaces to furniture design. Visualization commands one of the six rooms of the exhibit.

If you happen to be in New York City, it’s worth a visit!

You can now use visualizations on Many Eyes in much the same way as you use videos from You Tube or images from Flickr. Visualizations can be embedded by clicking the ’share this’ link and copying an html snippet into your site’s HTML code. We provide two preset sizes, but you can set any custom size by modifying width and height parameters in the embedding code.

We are looking forward to seeing how you, our users, use this capability! So go ahead, upload your favorite data, create a visualization and show it on your site or blog. Here are a couple of inspirational samples to get you started: