Data visualization for everyone: Many Eyes

Organizations and projects of all sizes have been dealing with more and more massively large datasets. Even “massively large” doesn’t mean a lot anymore. It might have meant a few hundred gigabytes five to ten years ago, and a few hundred megabytes not long before that. Now the large cutting-edge data-centric projects are working with multi-terrabyte datasets routinely. We have entered the Petabyte Age.

But what’s even more interesting than the fact that we now have the ability to work at such a scale at all is that datasets of this magnitude, and tools to begin to approach understanding them, are becoming available to the (at least technically-minded) community at large. And more and more instances of attempting to push such approaches to problem solving to the general public are appearing as well. I found this talk by Jeffrey Veen on “Designing for Big Data” to be quite thought-provoking. He discusses the novel shifts in the last few decades from data consumption to data production. This, along with the contemporary developments in storage and processing technology, has produced the unique time in which we live: a time in which people are beginning to be able to quickly and easy utilize large quantities of recent, relevant data to make everyday decisions. Sites such as EveryBlock, services like AWS’ Public Datasets, and countless other endeavors are changing the way we learn and live.

So what’s this Many Eyes business? Many Eyes is an IBM project, from the Collaborative User Experience group. I’ll appropriate one of their more poignant expressions as a description of purpose:

We believe that visualizations gain power when multiple people use them to communicate, and that communication gains power when multiple people can visualize and explore information together.

On the site, anyone can upload new datasets (or use the wide range already available; beware, there are plenty of junk ones, but more complete reliable ones as well), and try out any of a number of visualization styles. Once a style is selected and applied, you customize, name, tag, describe and publish your new creation! Each visualization is permanently available, allowing for embedded uses as well. Here’s a bubble chart of the percentage of population penetration in internet use that I made in two minutes:

Or check out this world map showing life expectancies. The graph interactions are quite interesting in themselves. I encourage you to try your hand at creating and sharing new visualizations. Such new forms of information accessibility will continue to provide benefits to more and more people. Not to mention they are quite fun to make!

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