The document discusses efforts to semantically annotate ocean observational data from the point of collection. This includes prototyping the annotation of SeaBird CTD data with RDFa and collaborating with sensor manufacturers to map file headers to SKOS concepts. The goal is to better describe and assess data quality for specific uses and enable (near) real-time linked data. Two approaches are outlined: building community semantics or reusing existing resources, with common ground being to embed semantics in OGC sensor web enablement documents.

1. Adam Leadbetter & Janet Fredericks

2. Overview
 Motivation
 Qartod to OGC
 Lake Ellsworth
 SenseOCEAN and future work
 Conclusions

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. Motivation
 Groundwork
 Prototyping SeaBird CTD XML with RDFa

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. 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. 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. 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. 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. Lake Ellsworth

11. SenseOCEAN

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. SeaDataNet

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. Conclusions

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. Conclusions

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. Conclusions

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