52 n ip 2011 geographic feature pipes


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52 n ip 2011 geographic feature pipes

  1. 1. Marcell Roth
  2. 2. Overview• Introduction• Motivation• Translating O&M and GML features to RDF• Example of Use• Conclusion21.06.2011 2
  3. 3. Introduction• OGC provides standards to encode vector data (GML features) and sensor data (as O&M)• Web of Data - Linked Data facilitates the exploration of related datasets – Raw data encoded in RDF – Resolvable URIs as names for things – Data is connected to another dataset using RDF links (Berners-Lee, 2006)• HTML vs. Linked Data – Hyperlinks connect documents w/o defining the relation – Linked Data allows linking datasets via typed relations• Huge geospatial datasets recently added to Web of Data – OpenStreetMaps http://linkedgeodata.org/ – Ordnance Survey http://data.ordnancesurvey.co.uk/.html21.06.2011 3
  4. 4. Motivation• Integration of geospatial data into the Web of Data is still missing!• Why Geographic Feature Pipes?«…a hosted service that lets you remix feeds and create new data mashups in a visual programming environment. The name of the service pays tribute to Unix pipelines, which make it easy to chain simple utilities together on the command line.» (Official Yahoo! Pipes Blog)21.06.2011 4
  5. 5. Outline• Intro• Motivation• Translating O&M and GML features to RDF• Example of Use – River Navigation• Conclusion21.06.2011 5
  6. 6. Translating O&M and GML features into RDFGeographic Feature Pipes (GFP)• Java API deployed as free proxy-based Web service• Allows for merging data from geospatial features and related sensor observations in one document• Supports complex queries in SPARQL• Increases the accessibility to non-OGC data sources21.06.2011 6
  7. 7. Translating O&M and GML features into RDFArchitecture based on Sesame21.06.2011 7
  8. 8. Translating O&M and GML features into RDF• Translation requires an ontological representation of the service• GI Source Ontology – Composed of Service Model Ontology and Data Model Ontology• SMO – Web service structural description – Based on Procedure-Oriented Service Model – http://www.wsmo.org/ns/posm/0.1/• DMO – Data model description21.06.2011 8
  9. 9. Translating O&M and GML features into RDF21.06.2011 9
  10. 10. Translating O&M and GML features into RDFGFP.Translator• O&M ontology – http://purl.org/ifgi/om# – Aligned to W3C’s Semantic Sensor Network (SSN) ontology• OGC Feature ontology – http://purl.org/ifgi/gml/0.2# – Based on OGC’s GML simple features profile (10- 100r2) – Geographic coordinates represented as WKT21.06.2011 10
  11. 11. Example of Use – River NavigationFind the navigable rivers for predetermined vessels• Observation data - SOS – River water level• River features - WFSExample: Get all the rivers in NRW with a depth >= 4 m21.06.2011 11
  12. 12. Conclusion & Future WorkConclusion• Service able to merge GML features & observations and publish them as Linked Data• Supports a more efficient geographic information retrieval• SPARQL allows powerful exploration & aggregationFuture Work• Raster data,...• Semantic annotations of the Data Models...21.06.2011 12
  13. 13. Thanks!Links• POSM: http://www.wsmo.org/ns/posm/0.1/• O&M ontology: http://purl.org/ifgi/om#• GML ontology: http://purl.org/ifgi/gml/0.2#• Geotools: http://www.geotools.org/• 52North OX-Framework: http://52north.org/communities/sensorweb/oxf/index.htmlContact• marcell.roth@uni-muenster.de21.06.2011 13
  14. 14. Features encoded in RDF21.06.2011 14
  15. 15. Sensor Data encoded in RDF21.06.2011 15
  16. 16. SPARQL Query21.06.2011 16
  17. 17. Merged Feature Properties21.06.2011 17