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Ride the Divide - race visualization

I watched Ride the Divide on Netflix tonight. It’s a really well put-together documentary about a mountain bike race from Banff, Canada, across the entire great divide, to the New Mexico-Mexico border. It features great photography and strong characters in these semi-nuts enthusiasts who take on the adventure, and turns out to be a pretty moving story.

It also has a bang-up cool race visualization:

Ride the Divide image
Ride the Divide image

The image features the relative positions of all the racers along the route — leaders, followers, and distance between them — their current altitudes, the mileage and location of the current subject, day of the race, relative distances to travel through each state, elevation of the overall route, and total travel distance for the entire race (2711 miles!). In a single, dense image, you get a ton of data. Quite cool.

Pics or it didn't happen

Pics or it didn’t happen

It’s May again (I know, I don’t know how that happened either, except that it followed April, and don’t get me started on April). Among other things, May is home to the “IronMan in May” competition at my place of work. The goal is to complete a sum of distances equivalent to an IronMan triathlon in the span of 31 days: 26 miles running, 2.4 miles swimming, and 112 miles biking. It’s a fun challenge and makes for a nice opportunity to mix up my workout routine, especially since I’m really, really not much of a runner.

And of course it means data to keep track of! There’s a paper chart on the wall at work, but who would want to use that when there’s such a glut of data visualization tools making the rounds now? Two years ago I used Joe Gregorio’s sparklines tool to plot my progress as I went:

Well it’s 2010 now (don’t get me started on 2009; that’s when I dislocated my shoulder — again — and then got nasty tendinitis to boot, so I didn’t take on IronMay last year), and this year I’m using Processing to plot my month’s data. Like R is really a programming language oriented to data-oriented programming, Processing is a language oriented around visualization (unlike R, however, which makes it easy to access vectors and data frames, Processing requires one to go back to array manipulation, so it took me some getting used to). Now, having seen the spectacular stuff in the Processing gallery I just hope that I’m not insulting the poor software by using it to make bar graphs (that look an awful lot like the old sparklines! I figured I had to start somewhere as I learned something brand new-to-me). This quick Processing tutorial is a great place to start.

Update May 31 2010: It’s a gorgeous day in Flagstaff and I knocked out the last of my run and bike miles on the urban trail this morning. Iron June, anybody?

Update shortly after the prior update: I wasn’t content with just the bar plot, so I tinkered just enough with streamgraph.js to come up with this (click through for the full-sized version at flickr):

IronMay 2010 - streamgraph

Pretty rad, I think.

Feelin' fine

Way cool:

(image page at flickr)

We Feel Fine aggregates and provides clicky-feely visualizations of expressions of emotions online, via text found in blogs, flickr pages and google.

I spent a good chunk of today trying to figure out why a single dumb plot was coming out all hinky; these guys have colored affect balls swirling apparently effortlessly around your mouse cursor. I feel inadequate, sure, but I feel wildly enthusiastic, as well. This is cool stuff.

(Via Chris at Ruminate.)


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