FlowingData, if you don't already read them: start now

FlowingData has a nice post today rounding up 20 data visualizations related to crime and criminals. Most revolve around maps with temporal components shoehorned into a few. We love maps here at Graphient. We love them for how they visually describe space, and we really love them for the way they provide a fixed contextual grid for organizing other kinds of data. The map visualizations presented at FlowingData stop short of adding in other data and stick to simply reporting the facts of crime, but those maps could have been used to introduce and connect all sorts of other (possibly sensitive) socioeconomic data and maybe tell a deeper story about crime.

Apparently, it’s free-for-all Friday here at Graphient. I just started using live search in TweetDeck for the word “visualization” and I feel like I jacked my head straight into the internerd. Also I drank a lot of green tea just now.

Ok, randomness is a really hard thing. Deriving actual randomness is hard work. A lot of mathematical models have been created over the years to describe randomness. Conveniently for you dear reader, this guy Daniel A. Becker has visualized a bunch of them for you. Enjoy this tasty and nutritious treat here.

Poisson Distribution. Look out Roger Mexico.

Ok, these probably won’t be daily. But they might be, since Data Visualization is so hot right now. Anyway, here’s an interactive map showing ridership of the NYC subway system from 1905 to now. The map is by Sha Hwang, a visual design technologist at Stamen Design in San Francisco. Check it out

Nice work, Mr Hwang.