I have spent much of the day compiling a bicycle data resource.
I am hopeful this will be a helpful micro-content resource for the OERu course Sport Informatics and Analytics.
Some time ago we used New York Citi Bike data as a practice for creating a neural network in R. I am keen to revisit this work and today’s research has been part of the project.
The new content includes:
- Fremont Bridge Bicycle Counter, Seattle
- Five articles written by Mike Logsdon
- Two articles by Jake Vandeplas
- News of Pronto Cycle Share Data
- The 2015 Pronto Data Challenge
- New York City Bike Share Data Discussions
- Washington DC Data
- Chicago Bike Share Data
- Hangzhou Bike Share Data
- Miami-Dade County Strava Data
- Eight Meta-Analysis Papers
I do think these data will be of interest for generic and domain specific data science activities. I found a 2014 paper by Jake Vandeplas a good place to start. He writes “this post is as much about how to work with data as it is about what we learn from the data” (original emphases).
The Bicycle November Project 10 & 11 (Mike Logsdon)