This project enhances Bicycle Networks’ RiderLog raw GPS tracked data captured via smartphones from all of Australia from May 2010 to May 2014, including 148,769 bicycle journeys undertaken by 9,727 bicyclists. These data have the potential to unravel macro patterns across Australian cities that can assist better understanding of human mobility and better planning of cycling infrastructure. However, in its raw format, the data are not suitable for any analysis or visualisation. As part of the High Value Collections Program funded by ANDS, this project developed several manual and automated data processing operations required to transform the data from the raw format to one that has good quality, validity, privacy and compatibility with digital analytical systems, such as geographical information systems (GIS) and statistical packages.
More detailed information can be found at: Leao, S. Z.; Lieske, S. N.; Conrow, L.; Doig, J.; Mann, V.; Pettit, C. J. Building a National-Longitudinal Geospatial Bicycling Data Collection from Crowdsourcing. Urban Science, 2017, 1 (3), 23; doi:10.3390/urbansci1030023.