If you are looking to do reproducible road traffic safety research,
please check out the stats19
package and accompanying paper
(Lovelace et al. 2019).
Welcome to bikeR, a store of code and example data underlying research into cycling and the associated risks.
The main branch of this work so far has been an analysis of STATS19, resulting in a paper published in the journal Transportation Research Part F: Traffic Psychology and Behaviour (Lovelace, Roberts, and Kellar 2016).
Of course, an open access version of the pdf is available online, here. The source code used to generate the paper can be found here.
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To allow others to perform the analysis conducted by me for West Yorkshire for other parts of Great Britain and perhaps the world, without reinventing the wheel.
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To help people learn R in general, an open source language for empowering oneself with the tools to extract meaning from data and make visualisations, like this one - see (Lovelace, Nowosad, and Meunchow 2019):
To be specific, the code used to produce this map in R can be found here: github.com/Robinlovelace/bikeR/blob/master/stat19/whereWards.R
- To encourage reproducibility, a conerstone of scientific research, in downloading road data (Padgham et al. 2017)
Lovelace, Robin, Malcolm Morgan, Layik Hama, and Mark Padgham. 2019. “Stats19: A Package for Working with Open Road Crash Data.” Journal of Open Source Software. https://doi.org/10.21105/joss.01181.
Lovelace, Robin, Jakub Nowosad, and Jannes Meunchow. 2019. Geocomputation with R. CRC Press. http://robinlovelace.net/geocompr.
Lovelace, Robin, Hannah Roberts, and Ian Kellar. 2016. “Who, Where, When: The Demographic and Geographic Distribution of Bicycle Crashes in West Yorkshire.” Transportation Research Part F: Traffic Psychology and Behaviour, Bicycling and bicycle safety, 41, Part B. https://doi.org/10.1016/j.trf.2015.02.010.
Padgham, Mark, Robin Lovelace, Maëlle Salmon, and Bob Rudis. 2017. “Osmdata.” The Journal of Open Source Software 2 (14). https://doi.org/10.21105/joss.00305.