Trajectory sequential patterns with regular expression constraints including spatial queries

"Moving object (MO) data representation and computing have received a fair share of attention over recent years from the database community. Replacing raw trajectory data (i.e., MO positions at different time instants) by sequences of application-dependent stops occurred at so-called places of interest (Pols) leads to the notion of semantic trajectories. Different techniques exist for sequential pattern analysis of trajectories defined in this way. One of them, RE-SPaM, expresses sequential patterns by means of regular expressions built not only over item identifiers, but also over constraints defined on the (temporal and non-temporal) attributes of the items to be analyzed. This analysis could be greatly enriched if spatial and non-spatial data associated with the MO are taken into account. In this paper we show how we can take advantage of the extensibility properties of RE-SPaM to augment its expressive power by allowing to include spatial queries in the constraints. For this, we make use of Piet, a framework allowing to integrate OLAP, GIS and MO data, and its associated query language denoted Piet-QL, providing a link between moving object data and their geographic environment."