High five to David Sparks for this Isarithmic History of the two party vote in America from 1920 to 2008. This is one of those cases where animation really tells the story of the data. The data is sampled at the county level and for the purposes of clear presentation has been spatially and temporally interpolated. Enjoy.

depressing, interesting

The New York Times has an interesting (and somewhat depressing) interactive times series graph of US unemployment rates. The controls let you slice the data demographically to get a sense of how groups you are not a part of might be feeling the effects of the recession. For the dryness of the presentation, this data tells a very compelling and human story.

geolocation + open data = awwesome

Coming across our desk via tweet from Sir Time Berneers Lee: an amazing (if not amazing looking) google maps based data mashup showing marine traffic throughout the world. That is to say, Real Time (not really but close) data showing position, speed and heading for ships throut the worlds major shipping lanes. The Mashup runs on top of a big open data set hosted by the Department of Product and Systems Design Engineering, University of the Aegean, Greece. More information about the project can be found at the open dot dot dot blog. Anyway go check it out.

One funny thing, it shows traffic on canals and rivers, so when you first look at the map you may wonder why there are forty boats in Missouri.

So, so cool.

The team behind the core technology that became photosynth is taking things to a much higher level. Sameer Agarwal and his band of computer vision desperadoes rebuilt Rome (or a reasonable simulation thereof) in just under 24 hours. This feat was pulled off using 150,000 images pulled from Flickr and some extremely hot computer vision research.

Check out the digest version here and the full nerd monty here.

By now, you have probably seen Sir Tim Berners-Lee talking about the importance of Open Data at this year’s TED conference. If you haven’t here it is. Take a look because it’s important:

I’m posting this now because the Open Data movement seems to be getting some traction–at least in Government circles. A couple of weeks ago the Obama administration launched Data.gov a clearing house for government data. Washington D.C. has become a leader in municipal public data, putting some 260 feeds of data out in raw form. And now the UK has decided to get in on the act: Gordon Brown the embattled Prime Minister, announced yesterday that none other than Sir Tim Himself would be heading up the initiative to open  England’s data up to the public.

This was largely damage control after a series of embarrassing disclosures about how members of Parliament expense things, but it is a welcome development all the same.

We here at Graphient wish Sir Tim the best of luck moving forward and very much hope that FreeTime will become the application of choice for those looking at all that data.

Read the BBC article here.

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.

I suppose Mr. Tran’s Sriracha concern can’t really be considered a startup anymore, But, it is an epic tale of capitalism. A company with humble roots overcoming epic adversity, including war (try that you web 2.0 feebs) to become the Heinz of hot sauce.

Read the NY Times article here and feel the burn.

Jer’s blog blprnt landed in my inbox this morning via google alert. He’s put together a pretty cool visualization in Processing by mining Twitter for the phrase “Just Landed” and then parsing out the location the tweeter had just landed in, along with the home location listed in their twitter profile. There are some problems with the assumptions made in the data collection process but, whatever. If Jer wants the science to be perfect than he’ll figure that out on his own.

The results of all that mining and processing look like this:

Awesome. Find out more about his methodology and check out some animation here.