Difference (from prior revision)
Changed: 25c25
The National Map data layers base map goes beyond the Ordinance Survey by including environmental and human use information. There is new, integrated, hydrology data is stored in Oracle and represented in owl. This set of data for 6 watersheds and 2 urban areas (St. Louis and Atlanta) will include all 8 data layers and become available for the watershed area. {nid 29SD}
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The National Map has multiple data layers, including environmental and human use information, on top of the base map that goes beyond other mapping efforts. There is new, integrated, hydrology data is stored in Oracle and represented in owl. This set of data for 6 watersheds and 2 urban areas (St. Louis and Atlanta) will include all 8 data layers and become available for the watershed area. {nid 29SD}
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Changed: 42c42
For example we can use it to calculate the distance between two points. We might do what Marco Neumann and Taylor Cowan did with their geosparql tool built on Google’s new app engine for java which extends Jena. This engine can process simple polygon searches for the concept of “near”. See http://geosparql.appspot.com/ for an online service. Todd notes that it uses an in-memory model so it may not scale to millions of triples, but Todd felt sure we could still make use of it on smaller datasets, such as we would start with. That is we could set up few smaller datasets and host these on Google appspot (e.g. http://appgallery.appspot.com/) just like Taylor did. We could then use it as another SPARQL endpoint in our demo. We could hardwire some queries to showcase this. {nid 29SL}
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For example we can use it to calculate the distance between two points. We might do what Marco Neumann and Taylor Cowan did with their geosparql tool built on Google’s new app engine for java which extends Jena. This engine can process simple polygon searches for the concept of “near”. See http://geosparql.appspot.com/ for an online service. Todd notes that it uses an in-memory model so it may not scale to millions of triples, but Todd felt sure we could still make use of it on smaller datasets, such as we would start with. That is we could set up few smaller datasets and host these on Google appspot (e.g. http://appgallery.appspot.com/) just like Taylor did. We could then use it as another SPARQL endpoint in our demo. (Simple a SPARQL endpoint is located by a URL on the Web that implements the SPARQL protocol. Generally this means that the URL can be sent queries.) {nid 29SL}
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Changed: 44c44
Todd and Eric have been in discussion on coordinating their efforts h Todd will meet with Eric while in Denver next week so they can mature these idea. They might work some examples that will moving this along from a relatively abstract use case to something more concrete. Part of this discussion might be about how to use sparql end points and rdf data coming back as query results. The use case might need another service to make it more “useful”, processing it into easier for novice users to understand etc. Under some scenarios we might use Geonames (http://www.geonames.org/ a geographical DB, covering all countries, holding over eight million place names for things like cities, villages, lakes, parks, hotels etc.), Open Street Maps and use Google Maps for images. (see January minutes for a discussion of an effort by USGS to leverage such vocabularies). An example of a simple demonstration using these is at http://3liz.org/geolocation/ {nid 29SM}
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Todd and Eric have been in discussion on coordinating their efforts. Todd will meet with Eric while in Denver next week so they can mature these idea. They might work some examples that will moving this along from a relatively abstract use case to something more concrete. Part of this discussion might be about how to use sparql end points and rdf data coming back as query results. The use case might need another service to make it more “useful”, processing it into easier for novice users to understand etc. Under some scenarios we might use Geonames (http://www.geonames.org/ a geographical DB, covering all countries, holding over eight million place names for things like cities, villages, lakes, parks, hotels etc.), Open Street Maps and use Google Maps for images. (see January minutes for a discussion of an effort by USGS to leverage such vocabularies). An example of a simple demonstration using these is at http://3liz.org/geolocation/ {nid 29SM}
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