Abstract: Spatial database systems and Geographic Information Systems as their most important application aim at storing, retrieving, manipulating, querying, and analysing geometric data. Research has shown that special data types are necessary to model geometry and to suitably represent geometric data in database systems. These data types are usually called spatial data types, such as point, line, and region but also include more complex types like partitions and graphs (networks). Spatial data types provide a fundamental abstraction for modeling the geometric structure of objects in space, their relationships, properties and operations. Their definition is to a large degree responsible for a successful design of spatial data models and the performance of spatial database systems and exerts a great influence on the expressive power of spatial query languages. This is true regardless of whether a DBMS uses a relational, complex object, object-oriented, or some other kind of data model. Hence, the definition and implementation of spatial data types is probably the most fundamental issue in the development of spatial DBMS. Consequently, their understanding is a prerequisite for an effective construction of important components of a spatial database system (like spatial index structures, optimizers for spatial data, spatial query languages, storage management, and graphical user interfaces) and for a cooperation with extensible DBMS providing spatial type extension packages (like spatial data blades and cartridges).
The goal of this tutorial is to present the state of the art in the design and implementation of spatial data types. First, we summarize the modeling process for phenomena in space in a three-level model and categorize the treatment of spatial data types with regard to this model. Then we pose design criteria for the types and analyse current proposals for them according to these criteria. Furthermore, we classify the proposed types and the operations defined on them from different perspectives. Our main interest is directed towards approaches which provide a formal definition of the semantics of spatial data types and which offer methods for their numerically and topologically robust implementation.