I’m working my way through a rather large RSS list at the moment (I’ve been working lots of stuff, so reading that and writing stuff here have both been somewhat curtailed)… but I’m determined to read the whole list, rather than just ‘mark all as read’.Anyway, I’m glad I did, as I found part 1 below and it made me want more than ever to do part 2…
Part 1 – visualising data
We have a funny relationship with data, and numbers. Some people love it, and can see the picture in data really quickly, almost like this here…
…and then some folk hate it, and much prefer the glory of the written word. Personally, I’m happy with both, though a wee bit better and happier with language.
Anyway, the numericists and the visualists can both be happy with the way the world is increasingly going, as people are increasingly taking the data we leave behind us (or ‘the data comet’, as first I described here), and using it to create beautiful wondrous things that allow you to see the picture, whether you’re a numericist or not.
Mashable had a great post here on 5 great visualisations of data, my favourite being the very elegant twitter stream visualisation SweetNTweet:
Worth a squizz, for sure.
But it made me think I should really do something about something I’ve been building up some data trails on in the last few weeks… #commutebox.
Part 2 – #commutebox
When I first started using Twitter hooked up to Facebook, I started mentioning on the train from Brighton to London each morning what I was listening to.
It seemed like a social thing to do.
Then Clare tweeted back that she was enjoying the morning musical update, which I liked the idea of… living viscerally through someone else’s commuting music.
“What if” I thought “lots of people did that, and you could see what all your friends were listening to on their commute in?”
To collate my own data as a start point, I began tagging the morning and evening music tweets with #commutebox (like ‘jukebox’…). A few more folk started doing it too (hello Neil, Dan, Mark, Erik, Graeme…).
I’ve not really found a great way visualise this data though, and just scroll through the twitter search function from time to time.
So, as a little project, I thought I’d try and achieve two things…
Firstly, get more data (mmmm, more data… must.. eat… data…).
Which means a few more people tweeting what they’re listening to on their commute, and suffixing it with #commutebox at the end. (hashtags are explained here)
That means YOU, the person reading this. Go on, give it a whirl. We thank you in advance 🙂
Secondly, I want to try and build/hijack/bodge together a decent visualisation tool for it all.
First thoughts run to something like the old style wall of time zone clocks you see in offices, or indeed in sixties movies when they’re trying to depict exactly how big and far apart the world is…
…so something like each city represented by it’s own centre, and maybe the #commutebox tweets eminating from them, not entirely unlike the SweetNTweet thing above.
So if anyone reading this has any thoughts on the best place to start, then the floor is yours. I shall start exploring properly too, of course, and Erik’s giving it some grey cell space when he can.
Anyway… why are we doing it?
Well, why not, as Shirky explained at the ICA…]]>