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.

Since our launch, we’ve been thrilled to see users contribute thousands of data sets and visualizations to Many Eyes. But as we watched the collection grow, we started to realize that we had an embarrassment of riches. With so many things to see and conversations to read, it’s getting to be hard to find your way around the site. One user email put it directly: “Time to organize the visualizations!”

In keeping with the spirit of the site, we’re turning to the collective intelligence of you, our users. Today we’re introducing a suite of features aimed at bringing the Many Eyes community together and letting you contribute to the site structure. We’ll discuss each feature in depth in the coming days, but here are the highlights:

Topic hubs: Now users can create miniature “portal pages” to collect data sets and visualizations on a particular topic or theme.
User profiles: Our old user pages were simply a list of activity. The new ones let you introduce yourself to the other people on the site and send messages to each other.

Ratings: Sometimes we see a great contribution and want to bring it to everyone’s attention. Now you can do that: the “rate it” button that’s underneath each visualization and data set. (If you see a mistake in a data set or misuse of a visualization technique–not that that ever happens –you can give a negative rating.) You can sort visualizations and data sets by rating, so the best ideas float to the top.

Watch lists: If you want to track activity related to a particular set of visualizations or data, use your new watchlist. When you go to your user page, you’ll see a single organized list of all the latest news.

There are many other new features and bug fixes, as well. Take the new site for a spin and tell us what you think!

We’re remodeling, and will be taking Many Eyes offline overnight. Thanks for your patience with the renovations, and we hope you like the new version when it’s unveiled.

We’ve updated a number of the visualizations on the site, in response to user requests. Changes affect the bubble chart, the treemap as well as the stack graph. In this post I will discuss these and give a couple of example uses. Look for more feature additions in the next few weeks (hello, sorting!)

Bubble chart

The old bubble chart looked pretty, but pretty blue. That seemed like an opportunity to show another dimension. Wouldn’t it be nice if you could color each of the bubbles by a categorical attribute? The examples below show a before-and-after: what happens when you color a bubble chart of the US budget to show budget categories.

You can combine coloring and aggregation to create a variety of other views, including some that look like miniature pie charts. These are experimental, and we’re interested in your feedback–and look for a more detailed discussion in a future blog post.

Treemap

The treemap previously required you to upload a numerical column with your hierarchical data. This had two disadvantages: In many cases, you might be simply interested in the number of items in each category. In other cases the treemap’s scaling can create tiny, hard to spot rectangles. The treemap below shows an overview of a backup log, but because the size is proportional to the number of bytes backed up, it contains a large number of tiny rectangles.

If we want to get an overview of the number of jobs run, instead of the number of bytes backed up we can choose ‘no selection’ for the size column, and the treemap will assign equal sizes to each log entry. We also let you color by categories, which makes the overall structure more clear. The image below shows the backup data using constant size and colored by hierarchy level (click for live version).

Stack Graph

You may have seen the reordering widget at the top of the treemap. Now we’ve incorporated that same widget in the stack graph for categories. In the sample below I reused the budget data to show the increases in planned US government spending. Rearrange the widget yourself to see the effect.

We encourage you to try out some of these improvements and see for yourself, so, stop reading this blog post and go play with some data!

Question: What do Pride and Prejudice, Swinburne’s poetry, and Green Eggs and Ham have in common?

Answer: Users of Many Eyes have uploaded word frequency data for each one.

One goal for Many Eyes was to find out just what kinds of data people wanted to visualize. In the past few weeks we’ve noticed a strong, unexpected trend: our users are extremely interested in looking at “unstructured” data sets, from Victorian poetry to the silliest Seuss, from a Ph.D dissertation to tags on del.icio.us. In response to this demand we’re happy to announce a new technique: an interactive tag cloud.

A tag cloud is a collection of words where the font size for each word corresponds to a numeric value, such as frequency. These purely verbal pictures are at least a decade old but have become something of a Web 2.0 emblem, visualizing the descriptive “tags” users attach to objects. Our tag cloud–created by ace intern Guilherme Boettcher–follows the standard model but adds a couple of features that make it more than an emblem.

You can do an instant, interactive search to narrow down the set of terms. As with all our visualizations, you can highlight sets of items to point out discoveries to other people. You can use a tag cloud on tabular data (a column of words and a column of numbers) but we’ve also revamped our data model to allow you to upload freeform text. That means we can do word frequency calculations for you, including removing common words across several languages and an option for finding two-word phrases. We also can show you the context of any word or phrase when you point to it with your mouse.
This technique still qualifies as experimental—and we encourage you to experiment! One excellent source of public domain books is Project Gutenberg. We’re curious to see what you come up with. (You can read this introduction for detailed instructions as well as a discussion of some of the pluses and minuses of the cloud technique.) And now that Many Eyes allows you to upload freeform text, look for more “unstructured” visualizations in the future.

On March 8th at 5 PM we will be talking about Many Eyes at the MIT Comparative Media Studies colloquium series. The CMS program is directed by Henry Jenkins, one of the top academic gurus of media and popular culture and someone we respect immensely.

We are excited to be able to discuss the vision and early-day usage of Many Eyes with the CMS folks. If you happen to be in Cambridge next week, be sure to check out the talk!

Welcome to the Many Eyes blog! This will be our home for talking about the site, announcing new features, and expanding on our vision for social uses of visualizations. We are very excited that you have decided to check out this experimental site!