Big Data and Cycling

Abstract

Big Data has begun to create significant impacts in urban and transport planning. This paper covers the explosion in data-driven research on cycling, most of which has occurred in the last ten years. We review the techniques, objectives and findings of a growing number of studies we have classified into three groups according to the nature of the data they are based on: GPS data (spatio-temporal data collected using the global positioning system (GPS)), live point data and journey data. We discuss the movement from small-scale GPS studies to the 'Big GPS' data sets held by fitness and leisure apps or specific cycling initiatives, the impact of Bike Share Programmes (BSP) on the availability of timely point data and the potential of historical journey data for trend analysis and pattern recognition. We conclude by pointing towards the possible new insights through combining these data sets with each other -and with more conventional health, socio-demographic or transport data.

Cycling as transport

“…It is important to recognise whilst Big Data clearly offers great knowledge-building potential, the veracity of the data (possible biases, noise, or abnormality in the data) presents ongoing difficulties to the users of these data. Additionally, we may know little about why a population exhibits certain travel patterns, and this supports one of the conclusions of Romanillos et al (2016), namely that we need to know more about the socio-demographics, attitudes, and motivation for travel behaviour. Much of these contextual data cannot be gleaned from a very large spreadsheet and instead rely on additional data collection techniques.…”

Examining travel patterns and characteristics in a bikesharing network and implications for data-driven decision supports: Case study in the Washington DC area

“…As a new form of mobility that gradually emerged, BSS has attracted much interest and attention in research. Analysis of surveys and data (Romanillos et al, 2016) have been performed by the operators and analysts who aim to achieve a better understand on the system states and key factors influencing the user experiences and the effectiveness of BSS, and on the role of BSS in transforming future urban mobility. Various aspects of bikesharing have been studied.…”

Digital technologies and the biomedicalisation of everyday activities: The case of walking and cycling

“…The economic processes of commodification identified by Clarke et al (2003) as core processes of biomedicalisation have been relatively neglected in the arena of digital technologies for walking and cycling. Markets for these products are large and increasingly entangled with other markets for commodified health: through health and other insurance markets; through sales of data to transport planners (Romanillos, Zaltz Austwick, Ettema, & De Kruijf, 2016); through the development of workplace health promotion (Meershoek & Horstman, 2016;Christophersen, Mørck, Langhoff, & Bjørn, 2015;Till, 2018) and through biomedical research (Munos et al, 2016), for example. There is, then, considerable potential for research which explores in detail how medical markets develop to incorporate 'mHealth' (Lupton, 2013) and, more specifically, documents who gains and who loses by the development of digital technologies.…”