F1 Data Junkie – Getting Started

Data is a wonderful thing, isn’t it…?! Take the following image, for example:

It depicts the racetrack used for the Bahrain Formula One grand prix last week, and it was generated from 2 laps worth of data collected at 1 second intervals from Lewis Hamilton’s car.

Long time readers will probably know that over the last couple of years I tried to track down bits of F1 motor racing related data, but to no real avail. Last year, I had the chance to look round the Red Bull Factory a couple of times (it’s located just a few minutes walk away from the OU campus in Milton Keynes) and chat to a couple of the folk there about possible outreach activites around data among other things (I’m still hopeful that something may come of that…).

Related to that possibility, we commissioned a rather nice gadget for displaying time series data against a map, in anticipation of getting car data we could visualise.

Anyway, ever impatient, when I saw that the Mclaren F1 website included a racetime dashboard, a Dev8D payoff in the form of a quick twitter conversation with @bencc resulted in him grabbing the last 30 or so laps worth of that data… :-)

I’ve had a quick play with it to see what sorts of thing might be possible (such as the map above), and there’s a whole bundle of stories that I think the data can turn up. I intend to explore as many of these stories as I can over the next few months, hopefully aided, abetted and corrected by a colleague from my department who is far better at physics than me… because the data contains a whole raft of physics related stories (and remember, folks: physics is fun).

If this: a) sounds like a turn off, but b) you claim to be interested in things like data journalism, please try to stick with the posts in this series (who knows – it may even turn into an uncourse;-) On the other hand, if you’re an F1 junkie (i.e. you follow @sidepodcast and/or listen to the Sidepodcast podcast;-) I’ll tag the posts f1data, so you can visit the tag page or grab the feed if you want to and not have to expose yourself to the rest of the ramblings that appear on this blog…

There’ll be no magic involved, though the results may turn out to be magical if you’re into geeky F1 stuff…;-) but to try and widen the appeal I’ll try to explore what stories the data holds about what’s happening to the car and driver, reflect a bit on what we can learn about extracting stories from data, and look to try to unpick the additional knowledge we might need to bring to the data in order to extract the most meaning from it; you can then see if these lessons apply to data – and stories – that you are interested in!

PS the F1 Fanatic blog is also doing a series on visualising and making sense of F1 related data, as this post on Bahrain Grand Prix FP2 analysis demonstrates. (See my own attempts at doing similar things with timing related data from last year: Visualising Lap Time Data – Australian Grand Prix, 2009). [UPDATE: As pointed out in the comments – and how could I have forgotten this?! (doh!) – there is also the F1 Numbers blog.]

Depending on how my F1 data related posts go, I may even try to hook up with the F1 Fanatic blog and/or the Sidepodcast folk to see if we can work together on ways of presenting this data stuff in a way that your everyday F1 fan might appreciate; just like T151 Digital Worlds helps your everyday computer game player appreciate just what’s involved in the design, development, business and culture of computer gaming:-) <- that’s a shameless plug if Christine or Mr C are reading…:-)