2010 is The Year of Information Visualization Theory. Here's why.

Terrible charts seem to be in season. Rarely have I come across so many incredibly bad charts in such a short time: information graphics that don't actually depict data, distorted representations, useless color schemes, and the worst pie chart ever.

With all the data that is now available, more powerful tools are needed to make more sense of it. Tableau Public provides some of the most powerful visualization tools available today, and it's free to use with public data.

Apple's iTunes Store is counting down to the ten-billionth (10,000,000,000th) song download. As in previous cases when they were running a download counter on their website, I am harvesting the data and visualizing it below.

Most data visualization on the web consists of static images. Typical interactive visualizations use Flash or Java, both of which have drawbacks and require plugins, don't work on mobile devices, etc. A number of recent visualization tools based on JavaScript promise to finally bring visualization to life on the web. The ways they work differ, but they all profit from recent advances in JavaScript performance across all modern browsers.

For some time now there has been some discussion about finding a new terminology for the Data Visualization field. The intention is to find names that reflects the two main different directions that are seen today on Dataviz: visual data analysis and data driven aesthetics images. The concern is that Data Visualization might lose its ‘serious’ role as an analytic tool by including works that, without doubt, praise aesthetics before clarity.

Pie charts are perhaps the most ubiquitous chart type; they can be found in newspapers, business reports, and many other places. But few people actually understand the function of the pie chart and how to use it properly. In addition to issues stemming from using too many categories, the biggest problem is getting the basic premise: that the pie slices sum up to a meaningful whole.