Data vis is not as easy as it looks!

| May 27, 2010

Keeping up with digital information can be overwhelming, what with the predicted 1,200 exabytes we will generate in 2010. That’s why data visualization is so important—it allows us to find meaning in that mumbled mess of information. It’s not as easy as people may think, though. It’s not about slapping some numbers into a graph machine and getting a histogram read out; there are a multitude of factors to take into account when deciding how to best represent the data. A survey of powerful visualization techniques, from the obvious to the obscure, gives you a detailed list of your data vis options. To quote from the paper:

Creating a visualization requires a number of nuanced judgments. One must determine which questions to ask, identify the appropriate data, and select effective visual encodings to map data values to graphical features such as position, size, shape, and color. The challenge is that for any given data set the number of visual encodings—and thus the space of possible visualization designs—is extremely large. To guide this process, computer scientists, psychologists, and statisticians have studied how well different encodings facilitate the comprehension of data types such as numbers, categories, and networks.

Check out the article for what the authors describe as a “visualization zoo”—a great resource for those of you into that sorta thang.