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Traditionally, GIS applications have had the ability to read or import a limited number of spatial data formats, but with few specialist ETL transformation tools; the concept being to import data then carry out step-by-step transformation or analysis within the GIS application itself. Conversely,
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industry to enable interoperability (or the exchange of information) between the industry's diverse array of mapping applications and associated proprietary formats. However, spatial ETL tools are also becoming increasingly important in the realm of
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as a tool to help organizations integrate spatial data with their existing non-spatial databases, and also to leverage their spatial data assets to develop more competitive business strategies.
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A common use of spatial ETL is to convert geographical information from a data source into another format that can be more easily used, for example by importing it into
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tools for processing non-spatial data have existed for some time, ETL tools that can manage the unique characteristics of spatial data only emerged in the early 1990s.
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spatial ETL does not require the user to import or view the data, and generally carries out its tasks in a single predefined process.
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Semantic processing: Ability to understand the rules of different data formats to minimize user input whilst preserving meaning
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within the GIS industry, many existing GIS applications are now incorporating spatial ETL tools within their products; the
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The transformation phase of a spatial ETL process allows a variety of functions; some of these are similar to standard
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Data dissemination: Ability to publish data via the internet or deliver by email regardless of source format
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Topological transformations: the ability to create topological relationships between disparate datasets
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Conflict management: Ability to manage conflicts between multiple users of the same data
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Data comparison: Ability to carry out change detection and perform incremental updates
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Spatial transformations: the ability to model spatial interactions and calculate
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411:"What is ETL… and How Can it Turn You into a Geospatial Rock Star?"
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characteristics of a feature, such as colour or line-style
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Desirable features of a spatial ETL application are:
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309:: Conversion between different data formats.
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287:: The removal of errors within a dataset
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