Random Etc. Notes to self. Work, play, and the rest.
Step 1: Can We Show It All?
I've been thinking recently about data visualisation approaches. One that I'm very fond of in the early stage of a project is to figure out a way to arrange the whole thing on screen – or a representative sample of it – and figure out what meaningful segments you can mark on top of it.
That was the rationale behind our Trulia Hindsight movies (show something about everything) and our charts of a day of activity on Digg. It's definitely an approach I've found easiest in Processing, although using it recently I've missed the instant mouse-driven interactivity of Flash or HTML.
My colleague Shawn just posted a visualisation he made to help debug a visualisation he's working on at the moment:
Shawn's chart is basically a simple scatter plot of cabspotting data points (by cab ID and time), except that he's also overlaid some of the connections between the data to show how far back and forward he has to look to accurately predict a cab's location. And the whole thing moves beautifully, showing up bad data and highlighting good data as it goes. Hopefully we'll get a video up soon.
In the meantime, be sure to read Shawn's description and keep an eye out for the final debugged visualization in the MOMA soon!
TimeContours
Nicholas Street, a recent MEng Computer Science graduate from Imperial College London, posted last week to the mysociety maps mailing list about his final year project work, TimeContours: Using isochrone visualisation to describe transport network travel cost.
His work includes a comparison with my own maps, which he says are "effective prototype implementations, but the unfamiliar unlabelled layout makes it difficult to relate to the underground". Touché! To his credit, Nicholas addresses almost all the deficiencies of my tube maps with his own software and goes significantly further in implementing the same kind of analysis for other transport networks (even including an example of using street data from my friends at OpenStreetMap).
His approach and background reading are covered in detail so the final paper will be a great resource for people working in this area in the future. I do hope he finds time to release the software for us all to use too. As well as the more traditional academic and print references, it's nice to see a hat tip to people putting their thoughts and experiments online such as myself, Rod and Oskar. Whilst a blog is no substitute for peer review and academic rigour, I strongly believe that the more of these ideas we share then the better all our work will become.
MySociety Travel Time maps of the UK
MySociety's Travel Time maps of the UK take a more rigourous and comprehensive look at the same kind of ideas I was exploring with my Travel Time Tube Map (and contours). Lovely results!
Tube Travel Contours
A variation on the tube map time travel applet, this version maintains the geographical layout but adds contours to show how long it takes to travel between stations. The contouring method isn't quite right (I should have used 1D textures), but it's good enough to experiment with.
Processing hacks: GPX library
This week toxi and I went live with Processing hacks, a wiki for documenting some of the more tricky, technical things that can be done with Processing.
I hope to chip away at the draft table of contents with an article or two a week until it's done. My first new code for the site is a basic Processing library for manipulating GPS data from GPX files. There are bound to be bugs and niggles, if you have a GPX file you could try it out with I'd be really grateful.
Here's an example app showing a friend's recent travels. Excuse the file name, as you can see the data is quite noisy and it needs some cleaning up. Also note that the Arcball class isn't quite working right (it needs fixing up for newer Processing versions), but it helps give you an idea of what's going on.
Biomapping Sketch
I've been looking at some of the data from Christian Nold's Biomapping project.
This new applet is a visualisation of GPS data from people walking on the Greenwich peninsula. The height of the mesh is a measure of GSR (Galvanic Skin Response, related to stress levels) at that point. See the Biomapping FAQ for more details, and note the emphasis on personal interpretation. Since I didn't split out the individual walks from the sample data this shouldn't really be considered an accurate map of stress in Greenwich!
Travel Time Tube Map
I've finally had time to get my Travel Time Tube Map applet to a presentable stage.
Here are a couple of screen shots to compare with Oskar and Rod.
There's a list of desired improvements on the applet page, but the next step for me is plotting this information on the Harry Beck style diagram rather than a geographic map. If anyone knows of a vector format tube map I could use to get me started, please let me know.
Maps, the Tube, and RDF headaches
Snowbound and carefree, I'm playing around with different methods of presentation for the ubiquitous London Underground (tube) map.
I found RGB versions of the tube line colours over at Rodcorp, so that saved me some bother.
Being the only machine-readable single-file resource I could find, I'm using Jo Walsh's RDF representation of the station locations and connections, a leftover from the sadly defunct MudLondon. I'm not sure yet if it's up to date, or complete, or internally consistent (reason number 1 in an ongoing series of why the semantic web might not be all that it's cooked up to be). Once I fix my doubtlessly buggy RDF parser and check with Jo for any pointers, I'll see if I can do better than this:
At least it's a start. If anyone has suggestions/links for alternative data sources I'd be very grateful - is there an electronic format schematic for the tube available from an official source? Aha - these CSV files from Wikipedia look more promising!
On with some alternative representations of the data - next stop: time to travel.
Arch-os vs Crystalpunks
I'm at the Crystalpunk Workshop for Soft Architecture, and yesterday the lovely Arch-OS folks introduced us to the streams of sensor data they collect from their building.
Here's a quick sketch which maps the temperature of their "Atrium B" floors onto the floors of the office block which houses the Crystalpunk Workshop. Wilfried calls it coloured goo, and who am I to argue?
Animated GPS Map
As part of the OpenStreetMap project, last month Steve Coast and I produced an A1 poster showing all the data we'd collected for London.
The biggest contributor to OpenStreetMap's UK data is an innovative courier firm called eCourier, and by way of thanks for their continuing commitment to the project I cooked up a movie of a sample of their data using Processing. Thankfully for me and my bandwidth, eCourier are kindly hosting it here for your enjoyment.
You can read more about our collaboration on their news page, and on the OpenStreetMap wiki.
Still wrestling with Feedwordpress here at Processing Blogs HQ. We're upgraded to 0.97, but something still strips links and images from Blogger feeds with mode="escaped" and I can't work out what it is. Much love and prizes to anyone who can spot the problem.
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