Spatial ETL, Mapping and SVG

The display of mapping data benefits greatly from the use of SVG (Scalable Vector Graphics). This paper describes the Spatial ETL (Extract, Transform, Load) technology that provides SVG map production capabilities for:

  • Desktop Users
  • Web-based data distribution systems
  • Application developers
  • A historical approach to converting data from over 100 different systems was to effectively write a different translator module for each format, with separate specifications for moving data to SVG. This approach was inflexible and restricted the resulting SVG so that it was dependent on both the structure and content of the input data, rather than just the content. Spatial ETL technology can translate data from over 100 different mapping formats and systems to SVG. This paper describes the design of a flexible Spatial ETL system that enables users to very easily produce custom SVG files.

    The first aspect in the design of a Spatial ETL system is to create a very flexible and rich data model that all the input formats simply populate. The second aspect in the system design is to provide a set of manipulation primitives. These primitives should, at a minimum, enable users to perform operations such as:

  • combining data from multiple input sources
  • selecting desired areas and themes
  • performing data overlays
  • reprojecting coordinates from one system to another

  • Using these design elements, the described system provides two types of Spatial ETL capabilities when writing to SVG.

    The first is called generic (also called thin-pipe translation), where the data is automatically moved from the input format to SVG. This adds little or no value to the data but provides a quick and easy way to get data from any of the systems to SVG.

    The second type of Spatial ETL is called semantic (also called thick-pipe translation), where users are provided with an environment for specifying the transformations that are applied to the input data as it is converted to SVG. Within this environment, users can restructure and combine data from different data sources and formats, and then output the results to SVG. This environment is what brings the full power of Spatial ETL to SVG map creation.

    The key to making semantic Spatial ETL possible is combining the very flexible data representation that completely characterizes all aspects of the data being read, with the environment for manipulating all of the data while creating SVG map files.

    Finally, to be effective, the system exploits capabilities of SVG by enabling the users to specify how events are handled. The system described in the paper enables users to define their own custom methods and then identify the method that is invoked for any of these SVG events:

  • Onfocusin
  • Onfocusout
  • Onclick
  • Onmousedown
  • Onmouseup
  • Onmouseover
  • Onmousemove
  • Onmouseout

  • The paper concludes by describing how the semantic Spatial ETL technology is used to satisfy needs of three different classes of users; specifically:

  • How the technology is deployed as a stand-alone application, enabling users to work at their desktops to easily create custom SVG map files;
  • How the technology can be deployed with any of the popular web-mapping tools, enabling them to export views of the data to SVG;
  • How this technology can be incorporated into any existing application that wishes to produce SVG map data from over 100 different source GIS systems.