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Integrating Government Data using Semantic Web technology  Dean Allemang Chief Scientist, TopQuadrant Inc.  Prepared for ISWC 2009
Government Data Sources ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
“ Objets trouv és” ,[object Object],[object Object],Lal Hitchcock Sculptures
“ Found data” ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Formats for “Found Data” in government Format Examples Notes Spreadsheets Data.gov, USASpending.gov, DOI Flexibility makes it popular, but makes work at re-use time XML Data.gov Not really a single format, but can be parsed uniformly RSS USASpending.gov, USGS Syntax wars largely irrelevant now.  Easy to read, dynamic RDFa <none?> New kid on the block, supported by Google, Yahoo!, Drupal SPARQL Endpoint Dbpedia.org Most flexible of all, dynamic RDF/N3/SKOS OEGov, Tetherless World Flexible, relatively static.  Great for vocabularies etc.
Quality Considerations of Found Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
A few species of Found Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Integration strategy using RDF ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Import data into RDF ,[object Object],[object Object],<Person id=“3”> <name>Irene Polikoff</name> <employer>TopQuadrant</employer> <position>CEO</position> </Person> Name Address Company Title Dean Allemang 10 Downing St. TopQuadrant Chief Scientist Michael Brodie 14 Wysteria Lane Verizon Chief Scientist
Import Data into RDF ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Canus Dog Collie Wolf Beagle Terrier Lone Steppen Genus Species Sub-species Canus Dog Collie Canus Dog Beagle Canus Dog Terrier Canus Wolf Steppen Canus Wolf Lone
Data Quality and Controlled Vocabularies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Quality and Controlled Vocabularies (cont) ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Unstructured data and  Controlled Vocabularies ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Merging Data ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data mapping Style 1:  Schema Mapping Examples ,[object Object],<Person id=“3”> <name>Irene Polikoff</name> <employer>TopQuadrant</employer> <position>CEO</position> </Person> Name=name,  but Company=employer Title=position Name Address Company Title Dean Allemang 10 Downing St. TopQuadrant Chief Scientist Michael Brodie 14 Wysteria Lane Verizon Chief Scientist
Schema Mapping Examples (cont) ,[object Object],<rss:item ID=“3”> <wgs:lat>39.945345</wgs:lat> <wgs:long>-79.34524</wgs:long> </rss:item> <image src=“doggie.jpg”> <wgs:Point> <wgs:lat>39.945345</wgs:lat> <wgs:long>-79.34524</wgs:long> </wgs:Point> </image> <Entry <position>39.945345,-79.34524</position> </Entry>
Schema mapping solutions: ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Schema mapping solutions (cont) ,[object Object],[object Object],[object Object],[object Object]
Role of Standards in the Mapping ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Data Mapping Style 2:  Tagging or Sorting ,[object Object],<Bookmark href=“http://www.topquadrant.com”> <tag>Semantic Web</tag> </Bookmark> <System name=“Central Bookkeeping”> <Evaluation> <PerformanceMeasure>Quality</PerformanceMeasure> <Resullt>Fair</Result> </Evaluation> </Bookmark> That’s an FEA reference! Where does this come from?
Role of Standards in the Mapping ,[object Object],[object Object],[object Object],[object Object],[object Object]
Analysis and Display ,[object Object],[object Object],[object Object],[object Object],[object Object]
Tags as Amalgamation FEA DOI GSA If two sources use the same controlled vocabulary, they can be amalgamated along that dimension.
Mapping Columns
Model-driven displays SELECT ?lat ?long WHERE {?item a :DisplayLocation . ?item geo:lat ?lat . ?item geo:long ?long .} Name latitude longitude Slausen -171.3 38.4 Union -171.4 38.2 Vine -170.9 37.9 McArthur -170.4 38.1 Anaheim -171.3 38.2 Chinatown -171.1 38.5 Beverly -171.3 38.1 latitude longitude Station domain geo:lat geo:long :DisplayLocation domain domain subPropertyOf subPropertyOf subClassOf
Exercises ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Integrating Government Data New

  • 1. Integrating Government Data using Semantic Web technology Dean Allemang Chief Scientist, TopQuadrant Inc. Prepared for ISWC 2009
  • 2.
  • 3.
  • 4.
  • 5. Formats for “Found Data” in government Format Examples Notes Spreadsheets Data.gov, USASpending.gov, DOI Flexibility makes it popular, but makes work at re-use time XML Data.gov Not really a single format, but can be parsed uniformly RSS USASpending.gov, USGS Syntax wars largely irrelevant now. Easy to read, dynamic RDFa <none?> New kid on the block, supported by Google, Yahoo!, Drupal SPARQL Endpoint Dbpedia.org Most flexible of all, dynamic RDF/N3/SKOS OEGov, Tetherless World Flexible, relatively static. Great for vocabularies etc.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23. Tags as Amalgamation FEA DOI GSA If two sources use the same controlled vocabulary, they can be amalgamated along that dimension.
  • 25. Model-driven displays SELECT ?lat ?long WHERE {?item a :DisplayLocation . ?item geo:lat ?lat . ?item geo:long ?long .} Name latitude longitude Slausen -171.3 38.4 Union -171.4 38.2 Vine -170.9 37.9 McArthur -170.4 38.1 Anaheim -171.3 38.2 Chinatown -171.1 38.5 Beverly -171.3 38.1 latitude longitude Station domain geo:lat geo:long :DisplayLocation domain domain subPropertyOf subPropertyOf subClassOf
  • 26.