Database Reference
In-Depth Information
Chapter 12
Trajectory Data Warehouses
The previous chapter focused on the analysis of the spatial features of static
objects such as stores, cities, or states, where by static we mean that the
spatial features of these objects do not change (or change exceptionally)
across time. However, there is a wide range of applications that require the
analysis of the so-called moving objects, that is, objects that continuously
change their position in space and time. This is called mobility data analysis.
The interest in mobility data analysis has expanded dramatically with the
availability of embedded positioning devices like GPS. With these devices,
trac data, for example, can be captured as a collection of sequences of
positioning signals transmitted by the cars' GPS along their itineraries. Since
such sequences can be very long, they are often processed by dividing them
in segments. For instance, the movement of a car can be segmented with
respect to the duration of the time intervals in which it stops at a certain
location. These segments of movement are called trajectories, and they are
the unit of interest in the analysis of movement data. Trajectory analysis can
be applied, for example, in trac management, which requires to monitor
and analyze trac flows to capture their characteristics. Other applications
aim at tracking the position of the users of social networks recorded by the
electronic devices they carry, like smartphones or tablets, in order to analyze
their behavior. As we have seen throughout this topic, data warehouses
and OLAP techniques have been successfully used for transforming detailed
data into valuable knowledge for decision-making purposes. Extending data
warehouses to cope with trajectory data leads to trajectory data warehouses,
which we study in this chapter.
We start this chapter in Sect. 12.1 motivating mobility data analysis. Then,
in Sect. 12.2 , we define temporal types, which provide a way to represent at
a conceptual level values that evolve in time, while in Sect. 12.3 we give a
possible implementation for these types in PostGIS. In Sect. 12.4 ,wepresent
the Northwind trajectory data warehouse. Finally, Sect. 12.5 is devoted to
querying trajectory data warehouses.
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