Sport Trackers and Big Data: Studying user traces to identify opportunities and challenges

Rudyar Cortés (1) , Xavier Bonnaire (2) , Olivier Marin (1) , Pierre Sens (1)

1 Regal - Large-Scale Distributed Systems and Applications
2 Departamento de Informatica [Valparaíso, Chile]

Personal location data is a rich source of big data. For instance, fitness-oriented sports tracker applications are increasingly popular and generate huge amounts of location data gathered from sensors such as GPS and accelerometers. Discovering new opportunities and challenges behind this kind of data requires knowledge about global user input in terms of volume, velocity, variety, and values. Gathering and analysing traces from a real world sports tracker service provides insight on these matters, but sport tracker services are very protective of such data due to privacy issues. We avoid this issue by gathering public data from a popular sports tracker server. In this paper, we present our database which is freely available online, and our analysis and conclusions from a big data perspective.

Mots clés: Sport Trackers; Personal Location Data; Big Data.

Domaines: Algorithme et structure de données [cs.DS]

Rudyar Cortés, Xavier Bonnaire, Olivier Marin, Pierre Sens. Sport Trackers and Big Data: Studying user traces to identify opportunities and challenges. [Research Report] RR-8636, INRIA Paris. 2014. ⟨hal-01092242⟩