Box 5.3

Key Application Services

Data Transformation — Data transformation services convert data between different formats and coding systems, between different spatial coordinate systems and projections, or between different levels of aggregation or disaggregation. Such services include certain types of image processing services that manipulate images from remote sensing instruments or aerial photography, geoparsing and geocoding services that convert location-based information (such as place names, addresses, and administrative and postal codes) to and from spatial coordinates, gridding algorithms that convert vector-based to raster-based data formats, and semantic translation services that facilitate interpretation of data between languages, disciplines, and applications.

Data Integration — Data integration services typically build on data transformations to support the assembly of data from different sources (for example, instruments, models, and disciplines) into a combined dataset or database or other derived product, such as a map. They can include linking services to identify data that have overlapping geographic coordinates or similar geographic features or characteristics, alignment services that adjust geometric models to improve spatial matching between different spatial datasets or images, and filtering services that select data for inclusion or exclusion on the basis of specified constraints and data characteristics.

Spatial and Statistical Analysis Spatial and statistical analysis services facilitate assessment of possible relationships within and between geographic distribu-

and greater reuse and repurposing of distributed data and services. Current approaches to SDI development, such as the Open Geospatial Consortium (OGC) Web Services Architecture (Whiteside, 2005), support an array of interoperable services focused on data transformation, integration, analysis and statistics, modeling, and visualization (see Box 5.3).

The SDI will need to adopt and implement an open Web services architecture and take a leadership role in establishing a framework for collaborative applications development and operations. For that to become a reality, the USGS will need to play a leadership role in establishing key elements of a community applications platform, including

• Specific open standards needed for data and service interoperability.

• Key reference datasets and parameters that would facilitate the interoperability and integration of data and services.

• Coordination mechanisms for ensuring development and implementation of new standards and reference datasets when and where needed.

• Mechanisms for quality control, measurement, and improvement.



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