We Have "Born Digital" - Now What About "Born Semantic"?

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Presentation at the European Geosciences Union General Assembly, 2014.

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We Have "Born Digital" - Now What About "Born Semantic"?

  1. 1. Adam Leadbetter & Janet Fredericks
  2. 2. Overview  Motivation  Qartod to OGC  Lake Ellsworth  SenseOCEAN and future work  Conclusions
  3. 3. Motivation  Bainbridge (2012) @ EGU  Cloud-based service-orientated data system for ocean observational data - an example from the coral reef community  Sparked the question  If we have so many observations, can we semantically annotate them from collection?
  4. 4. Motivation  Groundwork  Prototyping SeaBird CTD XML with RDFa
  5. 5. Motivation  Groundwork  Prototyping SeaBird CTD XML XML with RDFa  Synergy  Back in the office - contacting manufacturers  Work has already taken place!  Common goal  Dynamic, integrated data quality assessment
  6. 6. Domain Experts Sensor Mfgrs Operators IT Specialis ts Content Specifications/ SWE Implementation Model (Can it be an OGC Best- Practice?) What information is needed to assess quality of data and how do we implement it into an Sensor Observation Services (SOS)? Community-based Development
  7. 7. OWL/RDF Vocabularies/ ontologies SensorML Data HARVESTS REFERENCES RESOLVES DescribeSensor (SensorML) GetObservation (O&M) C L I E N T SOS Fredericks, Rueda, SWE2011
  8. 8. OWL/RDF Vocabularies/ ontologies SensorML Data SOS HARVESTS REFERENCE S RESOLV ES DescribeSystem (SensorML) GetObservation (O&M) C L I E N T<sml:output name="swell"> <swe:Quantity definition="http://mmisw.org/ont/mvco/properties/swell"> <swe:uom code="cm"/> </swe:Quantity> </sml:output>
  9. 9. Lake Ellsworth  Collaboration with sensor laboratory  Mapping from file header to SKOS concepts on NVS  Inserted into instrument firmware  Sadly project currently on hold
  10. 10. Lake Ellsworth
  11. 11. SenseOCEAN
  12. 12. SenseOCEAN  Collaboration with sensor laboratory / commercial manufacturers  Assign URLs to SKOS concepts from collection  Semantically annotated SensorML  Issues:  Data logger / communications bandwidth  Easy on a base station / mooring – not so on an AUV  Communicate changes in state only
  13. 13. SeaDataNet
  14. 14. Conclusions  Benefits  Data are described well enough for assessment of data quality for specified use and for a repurposed application from the point of collection  Hook into ontology development  O&M, PROV, Ocean Data Ontology
  15. 15. Conclusions
  16. 16. Conclusions  Benefits  Data are described well enough for assessment of data for specified use and for a repurposed application from collection  Hook into ontology development  O&M, PROV, Ocean Data Ontology  Moving into the realm of (near) real-time Linked Data
  17. 17. Conclusions
  18. 18. Conclusions  Two approaches  Community building of specific semantics  Or reuse of existing resources  Common ground  Embed semantics in OGC SWE documents  Not necessarily communicated across the full network  Mapped resources
  19. 19. Conclusions
  20. 20. Conclusions  Two approaches  Community building of specific semantics  Or reuse of existing resources  Common ground  Embed semantics in OGC SWE documents  Not necessarily communicated across the full network  Mapped resources  Take it to your communities! alead@bodc.ac.uk / jfredericks@whoi.edu

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