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.

Speeches by Obama versus speeches by Clinton. Blogs by men versus blogs by women. Song lyrics from the 80s versus lyrics from the 50s. The list of tag clouds on Many Eyes is a study in contrasts.

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!

Many Eyes will be down for some New Year’s maintenance tomorrow (Jan 5th) from 8 a.m. to 6 p.m. Eastern time. Sorry for the inconvenience — we’ll be back on Sunday.

You’ve asked for it and we listened! Until recently, interactive visualizations on Many Eyes could only be viewed on the site itself. Today we’re launching the ability to embed an interactive visualization from Many Eyes into your own blog, personal webpage or any other page you think makes sense. For example, if I wanted to show beer consumption per capita in the US in an interactive map, I can do so right here in this blog (click the visualization to load the live version).

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:

Many Eyes users have made maps of statistics ranging from beer consumption to teen births to the regional slang for those odd little bugs that curl into balls. But until now, users have been limited to maps of U.S. states and world countries.

Today we’re launching a revised set of maps. Using data provided by ESRI, Many Eyes now has state and province data for 14 countries, as well as a more detailed world map.

The maps also feature new ways to explore data. In addition to using color, you can set the map to show data values as overlaid circles or “bubbles”. The bubble view has the advantage that it gives each region equal attention, regardless of land area. You can also compare different columns of a data set directly, either with two side-by-side maps or through “small multiple” maps, showing every column of data at once in a grid of thumbnails.

It is also possible to show categorical data on the maps–such as the map showing the Brazilian regions below.

Finally, you’ll notice that regions are now labeled within maps. Some of you had asked for this feature and we agree that it’s long due.

So give the new maps a spin! We’ll be working on more country maps in the next few weeks. As always, we’re interested in your comments and feedback–and maybe even we’ll get to see a map of what those little curly bugs are called in Brazil.

Social data analysis–the kind of analysis supported by social interaction that happens on Many Eyes–is a new and exciting online phenomenon. In fact, a growing community is working to make data public and open up visualization technologies to everyone.

In the spirit of bringing together this emergent community, we joined forces with Maneesh Agrawala and Jeff Heer from Berkeley and are organizing a workshop at the CHI conference next year in Italy. The idea is to examine the design of social data analysis sites today, discuss the role of visualizations in these sites, and explore the different ways users are performing social data analysis.

If you are a researcher or practitioner whose work explores social data analysis and/or social uses of visualizations, consider submitting a position paper to the workshop.

The deadline for submissions is October 31 and directions on submitting a position paper are available on our workshop page.

Come join us in Italy!

Until now, data on Many Eyes was “frozen,” without any possibility of change. If you wanted to correct a mistake or add new data points, you had to upload a new, separate data set to the site and re-create all your visualizations.

Not anymore! Now you can edit any tabular data set you upload to Many Eyes, using a data editor created by intern Eric Gilbert. Any visualizations based on that data will use the most recent version of your data - ensuring that any changes are automatically reflected.

To edit a data set you’ve uploaded, go to the data set’s page and click on the “edit data set” button. There’s a variety of operations you can perform in edit mode, ranging from basic cell edits to more complicated transformations such as deleting entire rows and columns and applying functions to numeric columns.

Here’s an overview of the editing capabilities now available on the site:
- Change a cell value
- Add and delete rows and columns
- Change the sort order of the rows
- Look for possible problems by highlighting outliers and missing values
- Apply functions (like a logarithm) to a column, or divide one column by another

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For now you can only edit tabular data sets; free text data editing is not currently supported. And you can only edit your own data sets, though this may change in the future. Read our editing guide for a full description. And happy editing!

One of the joys of data analysis is the “aha” feeling when you figure out how different variables interact. Many of the visualizations on Many Eyes are good for inspecting the relationship between numerical variables–but until now there’s been a hole. How do you understand the relation between categories, things like political affiliations or occupations?

To fill this hole, the Matrix Chart was created by our talented intern Lee Byron. (You may already be familiar with his visualizations of music listening on last.fm.) This visualization, shown below, is a flexible and powerful way to make multivariate comparisons. It’s good for data with several non-numeric columns. For example, the matrix chart below shows data on members of the 17th Canadian Parliament, broken down by political party (y axis) and former occupation (x axis).

Here’s a second example, a visualization of NBA jersey colors. Not the most serious visualization on the site, but it does show off color customization, a first for a Many Eyes graphic.

You can read more about the technique here, and we’re collecting examples in a special topic hub, where we’ve put matrix visualizations of some existing data from the site. (One of the nice things about adding a new visualization is that it lets us revisit older data sets with a fresh pair of eyes.) You can leave comments or ideas for new features in the discussion area of the topic hub.

One last note for the technologists in the audience. This is our first experiment with Adobe Flash. We’re interested in your feedback on this as well–we’ll probably be conducting more experiments in the future.

I returned recently from the OECD World Forum on Statistics, Knowledge and Policy in Istanbul. It was invigorating to talk with such an impressive, globe-spanning group. Attendees–who ranged from academic statisticians, to medical researchers, to directors of government ministries–seemed genuinely excited by Many Eyes and its potential to aid policy decisions and educate citizens.

The OECD itself took the lead on using the Many Eyes technology: To coincide with the World Forum, they created an official OECD Topic Hub, with hundreds of datasets from the OECD Factbook 2007. As Enrico Giovannini, Director of Statistics and Chief Statistician of OECD, put it: “Global discussion based on solid statistics allows society to understand its current state and provides a base from which to make progress and innovate. Providing OECD’s 2007 Factbook data to the public offers citizens around the world an opportunity to collectively explore, discuss and tackle the societal challenges of our time.”

Today Many Eyes holds more than 100 visualizations of the OECD data, from oil prices to CO2 emissions. We encourage you to join the topic hub, create new visualizations, and contribute to the dialog around this trove of information. And we hope that other organizations will join the OECD in opening their data to the Many Eyes audience.