Hermessem: A semantic-aware framework for the management and analysis of our LifeSteps

Abstract

The explosion of available positioning information associated with the inferred or user-declared semantics of the respective locations, already contributes in what is called the big data era, posing new challenges to the mobility data management and mining research community. In this paper, motivated by a series of challenges set in [11], we present a unified framework for the management and the analysis of our LifeSteps, i.e. data objects that include both (raw) trajectories and their semantic counterpart. In particular, we provide solutions for developing real-world semantic-aware Moving Object Database (MOD) and Trajectory Data Warehouse (TDW) systems and we devise respective query processing algorithms. Our experimental study on synthetic data including synchronized raw (i.e., GPS log) and semantic (i.e., diaries) information, verifies the effectiveness and efficiency of the proposed framework.