Abstract
The datafication of everyday activities, such as leisure, is increasing, and large user-generated datasets are now available from a range of sources, including social media and recreation trackers. These datasets may provide valuable insights about recreation trends and allow planners to make data-driven management decisions. However, some scholars have noted that these data sources tend to highlight the experiences and preferences of only the majority of users, under-counting the experience of underrepresented groups, and therefore potentially reinforcing inequities that already exist within recreation spaces and jeopardising mobility justice. To explore the potential opportunities and limitations of such data, we analysed 5 years of bike data collected in two counties in the northeastern United States via the activity tracking app, Strava. We sought to explore whether analysis of Strava data could support decision-making for an emerging management challenge, namely whether to allow e-bikes in certain recreation spaces. Our analysis revealed that while the data are useful for highlighting general spatial and temporal trends, the format of the data restricts the deeper analysis required to answer more complex questions about causal relationships and ensure mobility justice for all user groups.
Mary Alldred
Associate Professor of Environmental Science
My research interests include nitrogen cycling, wetland ecology, urban ecology, and coastal management and restoration.