PPT on introduction to data warehouse and schemas

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PPTS on Data preprocessing and Spatial datawarehouse

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Spatial data types

Spatial Data Types

Several spatial data types can be used to represent the spatial extent of real world objects. , we use the spatial data types defined by the conceptual spatiotemporal model MADS ]. These data types and their associated icons are shown in diagram below As shown in the figure, these data types are organized in a hierarchy and provide support for two-dimensional features.

SimpleGeo is a generic spatial data type that generalizes the types Point, Line, and Surface. SimpleGeo is an abstract type, i.e., it is never instantiated as such: upon creation of a SimpleGeo value it is necessary to specify which of its subtypes characterizes the new element. A SimpleGeo value can be used, for instance, to generically represent cities, whereas a small city may be represented by a point and a bigger city by a simple surface.

ComplexGeo represents any heterogeneous set of geometries that may include sets of points, sets of lines, and sets of surfaces. ComplexGeo may be used, for instance, to represent a water system consisting of rivers (oriented lines), lakes (surfaces), and reservoirs (points). ComplexGeo, has PointSet, LineSet, OrientedLineSet, SurfaceSet, and SimpleSurfaceSet as subtypes.

Point represents zero-dimensional geometries denoting a single location in space. A point can be used to represent, for instance, a village in a country.

Line represents one-dimensional geometries denoting a set of connected points defined by one or more linear (in) equations. A line can be used to represent, for instance, a road in a road network. A line is closed if it has no identifiable extremities (in other words, its start point is equal to its end point)

OrientedLine represents lines whose extremities have the semantics of a start point and an end point (the line has a given direction from the start point to the end point). OrientedLine is a specialization of Line. An oriented line can be used to represent, for instance, a river in a hydrographic network.

 

Surface represents two-dimensional geometries denoting a set of connected points that lie inside a boundary formed by one or more disjoint closed lines. If the boundary consists of more than one closed line, one of the closed lines contains all the other ones, and the latter represent holes in the surface defined by the former line. In simpler words, a surface may have holes but no islands (no exterior islands and no islands within a hole).

SimpleSurface represents surfaces without holes. For example, the extent of a lake may be represented by a surface or a simple surface, depending on whether the lake has or not islands.

Several spatial data types are used to describe spatially homogeneous sets.

PointSet represents sets of points, which could be used to represent, for instance, the houses in a town.

LineSet represents sets of lines, which could be used to represent, for instance, a road network.

OrientedLineSet (a specialization of LineSet) represents a set of oriented lines, which could represent for instance, a river and its tributaries.

 SurfaceSet and SimpleSurfaceSet are used for sets of surfaces with or without holes, respectively, and are useful, for instance, to represent administrative regions.

Spatial Data warehouse

It is estimated that about 80% of the data stored in databases has a spatial or location component. Therefore, the location dimension has been widely used in data warehouse and OLAP systems. However, this dimension is usually represented in an alphanumeric, nonspatial manner (i.e., using solely the place name), since these systems are not able to manipulate spatial data. Nevertheless,it is well known that including spatial data in the analysis process can help to reveal patterns that are difficult to discover otherwise.

Spatial Databases: General Concepts

Spatial databases have been used for several decades for storing and manipulating spatial data. They allow us to describe the spatial properties of real-world phenomena.

There are two complementary ways of modeling spatial data in database applications. In the object-based approach, space is decomposed into identifiable objects and their shapes are described. This allows us, for example, to represent a road as a line or a state as a surface. The field-based approach is used to represent phenomena that vary over space, associating with each point in a relevant extent of space a value that characterizes a feature at that point. Typical examples are temperature, altitude, soil cover, and pollution level.

Spatial Objects

A spatial object corresponds to a real-world entity for which an application needs to store spatial characteristics. Spatial objects consist of a descriptive (or conventional) component and a spatial component. The descriptive component is represented using conventional data types, such as integer, string, and date; it contains general characteristics of the spatial object. For example, a state object may be described by its name, population, area, and major activity. The spatial component includes the geometry, which can be of various spatial data types, such as point, line, or surface,