Data Warehouses and GIS
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Data Quality
Data Quality Spatial Data Transfer Standard (SDTS)
Data Representations Data Models in Commercial GIS Systems
Data Types for Moving Objects Spatio-temporal Data Types
Data Types for Uncertain, Indeterminate, or Imprecise Spatial Objects Vague Spatial Data Types
Data Schema Application Schema
Data Structure
Data Warehouses and GIS JAMES B. P ICK School of Business, University of Redlands, Redlands, CA, USA
M ARCI S PERBER Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, USA
Synonyms
Synonyms
Definition
Algorithm
The data warehouse is an alternative form of data storage from the conventional relational database. It is oriented towards a view of data that is subject-oriented, rather than application-oriented. It receives data from one or multiple relational databases, stores large or massive amounts of data, and emphasizes permanent storage of data received over periods of time. Data warehouses can be spatially enabled in several ways. The data in the warehouse can have spatial attributes, supporting mapping. Mapping functions are built into some data warehouse packages. Online analytical processing (OLAP) “slicing and dicing” and what-if functions are performed on the data in the warehouse, and may include spatial characteristics. Furthermore, the data warehouse can be linked to geographical information systems (GIS), data mining and other software packages for more spatial and numerical analysis. Data warehouses and GIS used conjointly emphasize the advantages of each, namely the large size, time variance, and easy arrangement of data in the warehouse, along with the spatial visualization and analysis capabilities of GIS.
Definition A data structure is information that is organized in a certain way in memory in order to access it more efficiently. The data structure makes it easier to access and modify data. Main Text There are many types of data structures. Some examples are stacks, lists, arrays, hash tables, queues, and trees. There is not a data structure that is efficient for every purpose, so there are many different types to use for many different problems or purposes. A data structure should be chosen so that it can perform many types of operations while using little memory and execution time. An example of a good data structure fit would be using a tree-type data structure for use with a database. Of course there may be many data structures that can be used for a specific problem. The choice in these cases is mostly made by preference of the programmer or designer. Cross References Indexing, Hilbert R-tree, Spatial Indexing, Multimedia
Indexing Quadtree and Octree
Spatial data warehouses; Spatially-enabled data warehouses
Historical Background Although databases and decision support systems existed in the 1960s and the relational database appeared in the 1970s, it was not until the 1980s that data warehouses began to appear for use [1]. By 1990, the concepts of data warehouse had developed enough that the first major data
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