2. Overview
• Introduction
• Motivation
• Translating O&M and GML features to RDF
• Example of Use
• Conclusion
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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/.html
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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)
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5. Outline
• Intro
• Motivation
• Translating O&M and GML features to RDF
• Example of Use – River Navigation
• Conclusion
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6. Translating O&M and GML features
into RDF
Geographic 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
sources
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7. Translating O&M and GML features
into RDF
Architecture based on Sesame
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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 description
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10. Translating O&M and GML features
into RDF
GFP.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 WKT
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11. Example of Use – River Navigation
Find the navigable rivers for predetermined vessels
• Observation data - SOS
– River water level
• River features - WFS
Example: Get all the rivers in NRW with a depth >= 4 m
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12. Conclusion & Future Work
Conclusion
• Service able to merge GML features &
observations and publish them as Linked Data
• Supports a more efficient geographic information
retrieval
• SPARQL allows powerful exploration &
aggregation
Future Work
• Raster data,...
• Semantic annotations of the Data Models...
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