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Using linked data in a heterogeneous sensor web: Challenges, experiments and lessons learned
 

Using linked data in a heterogeneous sensor web: Challenges, experiments and lessons learned

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Presentation by Liang Yu during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).

Presentation by Liang Yu during the Sensor Web Ontology and Semantics paper session of the Sensor Web Enablement workshop (held during the 2011 Cybera Summit).

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    Using linked data in a heterogeneous sensor web: Challenges, experiments and lessons learned Using linked data in a heterogeneous sensor web: Challenges, experiments and lessons learned Presentation Transcript

    • Using Linked Data in aHeterogeneous Sensor Web:Challenges, Experiments andLessons LearnedLiang Yu and Yong Liu{liangyu, yongliu}@ncsa.illinois.edu National Center for Supercomputing Applications University of Illinois at Urbana-Champaign
    • Outline Ø Motivation and Goal Ø Using Linked Data for Integration Ø Services for Consuming Linked Data Ø An Example: Visualization Ø Conclusion and Future WorkImaginations unbound
    • Motivation •  Interoperability as a grand challenge in a Virtual Environmental Observatory •  The need to integrating different sensor data, citizen sensing, and other geospatial data etc. •  e.g., all river gage height values from all gages in Illinois between 1st May and 3rd May 2011. •  A heterogeneous Sensor Web is a reality •  Different protocols and formats, unknown semantics and no links. •  A paradigm shift: using Linked Data to build a Linked Sensor Web •  Linked data has the potential to provide a solution: URI naming system, HTTP protocol, RDF, links to other resources. •  E.g. an OGC SOS usually has no links to other resourcesImaginations unbound
    • Objective: Data Integration in a Virtual Environmental Observatory WaterMLImaginations unbound
    • Outline Ø Motivation and Goal Ø Using Linked Data for Integration Ø Services for Consuming Linked Data Ø An Example: Visualization Ø Conclusion and Future WorkImaginations unbound
    • A Simplified View of Linked Data •  Obtain sensors and observation data from sensors in Illinois Sensors Data States Illinois in Illinois Streamhttp:// http://sensorweb.ncsa.uiuc.edu/ sensorweb.ncsa.uiuc.edu/api/data/map/state/USGS/ Illinois sensordata/observations? observedBy.within=http:// sensorweb.ncsa.uiuc.edu/data/ map/state/USGS/Illinois http://sensorweb.ncsa.uiuc.edu/api/ sensordata/sites?within=http:// sensorweb.ncsa.uiuc.edu/data/map/state/ USGS/IllinoisImaginations unbound
    • Key Challenges •  Publishing Linked Data •  Re-publishing existing plain data to semantically linked data. •  Linking potentially “linkable data” together and enabling complex queries in a heterogeneous Sensor Web. •  Consuming Linked Data •  Serving data in an OGC RESTful SOS-like service. •  Tracking the provenance of Linked Data to facilitate trust and validation.Imaginations unbound
    • Workflow of Publishing and Consuming Linked DataRaw Data Linked Data Linked Data Geometric Tools Analysis LDA OntologyImaginations unbound
    • Republishing Data to RDF (1) •  Use XML as an intermediate format •  All non-XML data (Shapefile, Excel) are transformed to XML. •  Use XSLT to convert intermediate XML to RDF/XML •  Three different annotations are implemented in XSLT •  semantic annotation (rdf:type) •  outgoing links (to DBPedia), and •  provenance. •  Both syntactic transformations and semantic annotations are performedImaginations unbound
    • Republishing Data to RDF (2) provenance Outgoing linkrdf:typeImaginations unbound
    • Using Multiple OntologiesImaginations unbound
    • Creating Links by Geometric Analysis (1) •  To discover and create links between entities based on their spatial attributes. •  Different from previous work •  E.g.: http://www4.wiwiss.fu-berlin.de/bizer/silk/ •  Tools: Geotools (Java).Imaginations unbound
    • Creating Links by Geometric Analysis (2)Imaginations unbound
    • Provenance in Linked Data •  Where did the data come from? How were they processed? •  Using Open Provenance Model (OPM) Observation opmo:wasDerivedFromStar ssn:observedBy opmo:WasGeneratedBy Sensor opmo:wasDerivedFromStar <ssn:observedBy rdf:resource="http://sensorweb.ncsa.uiuc.edu/data/sensordata/sites/CUAHSI/ NWIS/03339000"/> <opmo:wasDerivedFromStar rdf:resource="http://waterservices.usgs.gov/nwis/iv"/>Imaginations unbound
    • Outline Ø Motivation and Goal Ø Using Linked Data for Integration Ø Services for Consuming Linked Data Ø An Example: Visualization Ø Conclusion and Future WorkImaginations unbound
    • Developing SOS with Linked Data API (1) •  An OGC RESTful SOS-like service over the integrated linked data •  Can be accessed by simple URLs. •  Is as flexible as SPARQL but with simpler syntax. q  Feature of Interest ( http://sensorweb.ncsa.uiuc.edu/data/map/watershed/USGS/2009_0) q  Single sensor site ( http://sensorweb.ncsa.uiuc.edu/data/sensordata/sites/CUAHSI/EPA/ MWRDSTOR:WW_39) q  Collection of sensor sites (http://sensorweb.ncsa.uiuc.edu/api/sensordata/sites) q  Single observation ( http://sensorweb.ncsa.uiuc.edu/data/event/hail/noaa/ 2010/10908_2010-12-31T22:40:00) q  Collection of observations ( http://sensorweb.ncsa.uiuc.edu/api/sensordata/observations)Imaginations unbound
    • Developing SOS with Linked Data API (2) •  Obtain all the sensor sites within Illinois state. •  http://sensorweb.ncsa.uiuc.edu/api/sensordata/sites?within=http://sensorweb.ncsa.uiuc.edu/data/ map/state/USGS/Illinois items": [ {"_about": " http://sensorweb.ncsa.uiuc.edu/data/sensordata/sites/CUAHSI/EPA/MWRDSTOR:WW_39", "hasCode": "MWRDSTOR:WW 39", "hasLocation": { "lat": 41.88185119628906, "long": -87.63558197021484, "type": "http://www.w3.org/2003/01/geo/wgs84_pos#Point"}, "hasName": "South Branch Chicago River @ Madison St.", "hasNetwork": " http://sensorweb.ncsa.uiuc.edu/data/sensordata/network/CUAHSI/EPA", "hasStream": " http://sensorweb.ncsa.uiuc.edu/api/sensordata/observations?observedBy=http:// sensorweb.ncsa.uiuc.edu/data/sensordata/sites/CUAHSI/EPA/ MWRDSTOR:WW_39", "type": "Sensor", "wasDerivedFromStar": "http://water.sdsc.edu/waterOneFlow/", "within": [" http://sensorweb.ncsa.uiuc.edu/data/map/county/USGS/Cook_County,_IL"," http://sensorweb.ncsa.uiuc.edu/data/map/state/USGS/Illinois"," http://sensorweb.ncsa.uiuc.edu/data/map/watershed/USGS/2009_2627"]},Imaginations unbound
    • Outline Ø Motivation and Goal Ø Using Linked Data for Integration Ø Services for Consuming Linked Data Ø An Example: Visualization Ø Conclusion and Future WorkImaginations unbound
    • An Example Application (Visualization of SOS Results) •  Visualization Platform: WWT (World Wide Telescope)|Earth •  Sensor Data: river gage height values produced by gages in Illinois between 2011-05-01 and 2011-05-03. q  http://sensorweb.ncsa.uiuc.edu/api/sensordata/observations?observedBy.within=http:// sensorweb.ncsa.uiuc.edu/data/map/state/USGS/Illinois&_sort=observationResultTime.inXSDDateTime&min- observationResultTime.inXSDDateTime=2011-05-01T00:00:00-05:00&_page=0&max- observationResultTime.inXSDDateTime=2011-05-03T00:00:00-05:00&observedProperty=http:// sensorweb.ncsa.uiuc.edu/data/property/USGS/NWIS:UnitValues/00065Imaginations unbound
    • Outline Ø Motivation and Goal Ø Using Linked Data for Integration Ø Services for Consuming Linked Data Ø An Example: Visualization Ø Conclusion and Future WorkImaginations unbound
    • Conclusion •  A “Linked Sensor Web” solution for integrating heterogeneous sensor data sources and geospatial data. •  A best practice of using W3C SSN ontology as well as other domain ontologies. •  A method to discover and create links among spatial data. •  Using Linked Data API to provide OGC RESTful SOS-like services •  http://sensorweb.ncsa.uiuc.edu/api-list.html •  Tracking provenance data and managing them using OPM.Imaginations unbound
    • Future Work •  Towards Linked Geostreaming Data •  Tuning the performance •  Facilitating searching and crawling of Linked data •  End-to-end provenance managementImaginations unbound
    • Acknowledgements Ø Microsoft Research Connections Ø  “Environmental Informatics” Program Ø  Institute for Advanced Computing Applications and Technologies at the University of Illinois at Urbana- Champaign Ø  “Virtual Observatory for Sustainability of Intensively Managed Environmental Systems” ProjectImaginations unbound