Spatial and spatio-temporal data models and languages

A data model provides a formalism consisting of a notation for describing data of interest and of a set of operations for manipulating these data. It abstracts from reality and provides a generalized view of data representing a specific and bounded scope of the real world. In the context of databases, a data model describes the organization, that is, the structure, of a database. In the context of complex objects like video, genomic, and multimedia objects, a data model describes a type system consisting of data types, operations, and predicates. Spatial and spatio-temporal data models are of this second kind. A spatial data model is a data model defining the properties of and operations on static objects in space. These objects are described by spatial data types like point (for example, representing the locations of cities in the U.S.), line (for example, describing the ramifications of the Nile Delta), and region (for example, depicting school districts). Operations on spatial data types include, for instance, the geometric intersection, union, and difference of spatial objects, the computation of the length of a line or the area of a region, the test whether two spatial objects overlap or meet, and whether one object is north or southeast of another object. A spatio-temporal data model is a data model representing the temporal evolution of spatial objects over time. These evolutions can be discrete, that is, they happen from time to time (for example, the change of the boundary of a land parcel) or continuous, that is, they happen permanently and smoothly (for example, the devastating trajectory of a hurricane). In the continuous case, one speaks about moving object