How does one select the "right" or "best" way to visually represent data? Of course, the short answer is it depends. (In fact, that theoretical manner might not even exist.)
Beyond that, it's an interesting question and, as I argue in The Visual Organization, a harder one to answer these days for two reasons. First, there's just so much more data flying around today. Second and in a related vein, there are more ways to represent this information.
Against that backdrop, wouldn't it be useful to consult a dataviz guide? A visualization of the different types of visualizations available to us (read: a metavisualization)?
Originally, this project was a way for me to develop my own knowledge of data visualization and create a reference tool for me to use in the future for my own work. However, I thought it would also be useful tool to not only other designers, but also anyone in a field that requires the use of data visualization regularly (economists, scientists, statisticians etc).
Or, visually speaking:
This is just a sample of the types of data visualizations that anyone with some data and basic computer fluency can create. The site contains many more – with more coming soon (as evinced by the gray colors of bubble charts, arc diagrams, etc.) Think of these types of tools as starting guides for finding an ideal way to convey the meaning of data and, just as important these days, to encourage data exploration and discovery.
Projects like the dataviz catalogue underscore the fact that we have entered a more democratic and transparent information era. Open data, mobility, big data, cloud computing, APIs, SDKs and other trends are all converging.
Brass tacks: It's high time for everyone in organizations to think about the data that they visualize – and how they visualize it. Tried-and-true methods may have worked ten or even five years ago. Foolish is the organization that is stuck in the "set it and forget it" mindset.
What say you?