MASTER: A Multiple Aspect View on Trajectories

For many years trajectory data have been treated as sequences of space-time points or stops and moves. However, with the explosion of the In- ternet of Things (IoT) and the flood of Big Data generated on the Internet, like weather channels and social network interactions that can be used to enrich mobility data, trajectories become more and more complex, with multiple and heterogeneous data dimensions. The main challenge is how to integrate all these information with trajectories. In this paper we introduce a new concept of tra- jectory, called multiple aspect trajectory, propose a robust conceptual and logi- cal data model that supports a vaste range of applications, and differently from state-of-the-art methods we propose an efficient storage solution for efficient multiple aspect trajectory queries. The main strength of the model is the com- bination of simplicity and expressive power to represent heterogeneous aspects, ranging from simple labels to complex objects. We evaluate the proposed model in a tourism scenario and compare its query performance against SECONDO extension for symbolic trajectories. This is the peer reviewed version of the following article: dos Santos Mello, R, Bogorny, V, Alvares, LO, et al. MASTER: A multiple aspect view on trajectories. Transactions in GIS. 2019; 23: 805– 822. https://doi.org/10.1111/tgis.12526 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1111/tgis.12526 This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.