A Data Foundation For The National Spatial Data Infrastructure (1995) / Chapter Skim
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1 INTRODUCTION
1 INTRODUCTION
Pages 5-14
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The Mapping Science Committee (MSC) focuses its attention on a particular type of data spatially referenced digital data.
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Many of the production activities will take advantage of the capabilities of the private sector through contracts and other arrangements; to a certain extent, market forces will further push the production, maintenance, and distribution of certain data sets. This report: identifies three categories of spatial data that form the foundation for the NSDI, identifies minimum specifications required to integrate other spatial data with the foundation, and recommends specific activities that should be pursued to achieve an integrated and accessible NSDI.
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These analyses may require real-t~me animation, scene comparison, data overlay, buffering, and other operations that cannot be supported by analyses of paper maps alone. This is not to say that paper maps are no longer needed but rather that their production should no longer be the primary driver for spatial data production.
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Seemingly endless technical issues, such as differences in data models, data content, data quality, and data transfer must be resolved. Attention must be given to the problems of data redundancy, standards, and training in the new technologies.
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An analytical system supported by digital spatial data could have determined routes of drainage and water absorption by soils and substructures. In addition, automatic traffic routing at each stage of flooding could also have been supported, allowing emergency services and commercial transportation planning to be put in place before crises of street and bridge loss occurred.
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Table ~ presents examples of spatial data applications and their corresponding precision or resolution requirements. To provide the necessary assurances of data quality, data sets may be evaluated according to guidelines and strategies set forth in the Spatial Data Transfer Standard (SDTS; F1PS Publication 17351-.
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CHALLENGE OF DATA INTEGRATION The sharing of spatial data involves more than just ensuring that data are in digital form and that the metadata (information on data quality, accuracy, lineage, currentness, etc.) are included with the spatial data.
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12 A Data Foundation for the NSD! shoreline mapped @ 1:4000 shoreline mapped @ 1:24000 shoreline mapped @ 1:24000 "A Off!
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Integrating data can require merging position, merging attribute categories, correcting geometry or topology, and/or revising data definitions to embed the contents of one data set into another. Data integration is not solely limited to positional registration.
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It is advantageous to adopt a single reference strategy and integrate data for any application to that reference, to minimize integration costs. For the nation as a whole, if each data producer relied on a different reference, data sharing, data exchange, and data integration would be impeded.
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