The document discusses using linked data to integrate heterogeneous sensor data sources and geospatial data in a sensor web. It describes challenges in publishing and consuming linked data, and developing a RESTful sensor observation service (SOS) over the integrated linked data. An example application visualizes river gage height values from Illinois using the World Wide Telescope. Future work areas include linked geostreaming data, performance tuning, and end-to-end provenance management.

1. Using Linked Data in a
Heterogeneous Sensor Web:
Challenges, Experiments and
Lessons Learned
Liang Yu and Yong Liu
{liangyu, yongliu}@ncsa.illinois.edu
National Center for Supercomputing Applications
University of Illinois at Urbana-Champaign

2. 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 Work
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3. 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 resources
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4. Objective: Data Integration in a Virtual
Environmental Observatory
WaterML
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5. 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 Work
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6. A Simplified View of Linked Data
• Obtain sensors and observation data from sensors in
Illinois
Sensors Data
States Illinois
in Illinois Stream
http:// 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/Illinois
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7. 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.
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8. Workflow of Publishing and Consuming
Linked Data
Raw Data Linked Data Linked Data
Geometric
Tools Analysis
LDA
Ontology
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9. 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
performed
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10. Republishing Data to RDF (2)
provenance
Outgoing
link
rdf:type
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11. Using Multiple Ontologies
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12. 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).
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13. Creating Links by Geometric Analysis (2)
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14. 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"/>
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15. 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 Work
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16. 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)
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17. 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"]},
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18. 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 Work
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19. 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/00065
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20. 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 Work
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21. 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.
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22. Future Work
• Towards Linked Geostreaming Data
• Tuning the performance
• Facilitating searching and crawling of Linked data
• End-to-end provenance management
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23. 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” Project
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