Trajectory data management: A data model and predicate logic with operators for spatio-temporal query processing

With recent sensor and tracking technology advances, the volume of available trajectory data is steadily increasing. Consequently, managing and analyzing trajectory data has seen significant interest from the research community. The challenges presented by trajectory data arise from their spatio-temporal nature as well as the uncertainty regarding locations between sampled points. In this paper, we present a formal spatio-temporal predicate logic with configurable strictness parameters and two novel operators: (1) a spatio-temporal selection operator for filtering trajectories, and (2) a spatio-temporal crop operator for extracting relevant sub-trajectories based on spatio-temporal predicates. Furthermore, we integrate a similarity-based join operators for flexible trajectory comparison. Finally, we show that our predicate logic is expressive enough to capture all spatial and temporal relations put forward by previous work. • A trajectory data model based on NF 2 equally emphasizes spatial, temporal, and application-specific attributes. • Unified spatio-temporal predicate logic supports flexible strictness to handle data uncertainty. • Predicate logic integrates DE-9IM spatial and Allen’s Interval Algebra temporal relations. • New similarity join predicates enable advanced trajectory data analysis. • Demonstrated handling of trajectory data uncertainty in query operations.