This document summarizes a presentation about analyzing and visualizing London bike share data. It describes gathering over 400,000 data points from the bike share API over 48 hours, which was difficult to analyze and plot in Excel due to the large volume. It then discusses filtering, cleaning, and optimizing the data for computation before determining how to represent it. The presentation demonstrated visualizing the data using Processing and relied on bike IDs obtained through a Freedom of Information request. Further information is provided on the presenter and related projects.

1. Of Bikes & Bits
Brock Craft
London Knowledge Lab

2. a tale of laziness
~50 metres/165 feet

3. :-(

5. Sachin Handiekar
http://api.bike-stats.co.uk/service/rest/bikestats?format=[xml | json | csv | yaml]
http://api.bike-stats.co.uk/service/rest/bikestat/dockID?format=[xml | json]

6. Theobald’s Road

7. 48 hours, in Excel:
over 400 stations
216,192 rows
2,160,000 data items
hard to plot
and not very pretty

8. user requirements
gathering
selecting what’s relevant (filtering)
cleaning the remainder
optimising for computation
determining representational semantics
the demo part...

9. http://processing.org

10. Oliver O’Brien, Martin Austwick

11. relies upon bike IDs
required FOI request

13. Further info...
Dr Brock Craft, London Knowledge Lab
http://www.brockcraft.com, @thatbrock
http://www.lkl.ac.uk
http://api.bike-stats.co.uk
http://processing.org
http://oobrien.com/vis/bikes/?city=london
(Oliver O’Brien’s mashup)