  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 data model that treats trajectories as first-class
citizens, thus fully capturing their spatio-temporal properties. We also
introduce a predicate logic that enable query processing under different
uncertainty assumptions. Finally, we show that our predicate logic is
expressive enough to capture all spatial and temporal relations put forward by
previous work.
