The great thing about being a graduate student is that you get to experiment. Anita Lillie, from the MIT Media Lab, demos MusicBox, her master’s thesis project that visualizes and maps music collections based on songs’ acoustic features. As might be expected, she uses principle components analysis to arrange songs. Each dot represents a song. If two songs sound similar, they should appear close to each other. As an example, the above dots are colored by music genre. Rap songs appear on the left in red while classical appears on the right.
As an aside, Anita’s project reminds me a lot of a GGobi demo by Di Cook. She used the tuneR library in R to quantify Beatles songs and then used GGobi to do something similar to MusicBox. R and GGobi are free to use, so if you’re interested in visualizing your own music library, you might want to check them out.
[via TechCrunch]

I thought this was a joke when I first read it, but scientists from Japan’s ATR Computational Neuroscience Laboratories have developed software that can map brain activity to an image. Subjects were shown letters from the word neuron and images were reconstructed and displayed on a computer screen.
One of the more painful parts of analysis or visualization is that you have to get the data in a proper format. Real data almost never comes how you want it.
It was really only a matter of time, but Amazon now hosts


Visualize This: The FlowingData Guide to Design, Visualization, and Statistics (2nd Edition)
