Presentation to OGC Geosemantics Summit, 2015-06-03. I explain the incompatibiity between the Observation classes in SSN and O&M, and how this can be understood mostly clearly through alignment with PROV. Compared with other 'upper ontologies' PROV provides a very easy to understand framework, with only 3 top level classes, two of which are disjoint.

1. Ontology alignment
– is PROV-O good enough?
Simon Cox | Research Scientist | Environmental Information Infrastructures
3 June 2015
LAND AND WATER
Geosemantics Summit – OGC TC, Boulder, CO, USA - 2015-06-03

2. Outline
• Upper ontologies
• O&M vs SSN
• Alignment strategy
Ontology alignment using PROV | Simon Cox2 |

3. Ontology alignment using PROV | Simon Cox3 |
Upper ontologies
http://www.disi.unige.it/person/MascardiV/Download/DISI-TR-06-21.pdf

4. General Formal Ontology
Ontology alignment using PROV | Simon Cox4 |

5. Basic Formal Ontology
Ontology alignment using PROV | Simon Cox5 |

6. DOLCE ultra-lite
Ontology alignment using PROV | Simon Cox6 |

7. Ontology recapitulates ideology
Ontology alignment using PROV | Simon Cox7 |

8. PROV
Ontology alignment using PROV | Simon Cox8 |

9. OM_Observation
+ phenomenonTime
+ resultTime
+ validTime [0..1]
+ resultQuality [0..*]
+ parameter [0..*]
GF_PropertyType
GFI_Feature
OM_Process Any
+observedProperty
1
0..*
+featureOfInterest
1
0..*
+procedure1 +result
Range
An Observation is an action whose result is an estimate of the value
of some property of the feature-of-interest, obtained using a specified procedure
ISO 19156 Observations and Measurements
9 | Ontology alignment using PROV | Simon Cox
Cox, OGC Abstract Specification – Topic 20: Observations and Measurements 2.0
ISO 19156:2011 Geographic Information – Observations and measurements

10. om:Observation using ISO 19105-2 rule
Ontology alignment using PROV | Simon Cox10 |
(TopBraid diagram view)

11. O&M integrated into ISO framework
Ontology alignment using PROV | Simon Cox11 |
Direct ISO dependencies
• gf - Feature ISO 19109
• cv - Coverage (fields) ISO 19123
• md - Metadata ISO 19115
• gm - Geometry ISO 19107
• tm - Temporal ISO 19108
• h2o - Meta-model ISO 19150-2
• basic - Datatypes ISO 19103
Required ISO UML models converted to OWL
No other alignment attempted at this time

12. om-lite
Ontology alignment using PROV | Simon Cox12 |
Sem. Web. Journal – in review

13. SSN Ontology
Ontology alignment using PROV | Simon Cox13 |

14. SSN aligned with DOLCE ultra-lite
Ontology alignment using PROV | Simon Cox14 |
Is Observation a Social Object, or an Event?
Sensing vs. Reasoning?

15. PROV
Ontology alignment using PROV | Simon Cox15 |

16. Ontology alignment using PROV | Simon Cox16 |
Compton, Corsar & Taylor, Sensor Data Provenance: SSNO and PROV-O Together at Last. SSN2014

17. om-lite aligned to PROV-O
Ontology alignment using PROV | Simon Cox17 |
Cox, Basic Observations and Sampling Feature Ontology . Semantic Web J. (submitted)

18. SSN Observation vs O&M Observation
ssn:Observation subClassOf prov:Entity
BFO Continuant
om:Observation subClassOf prov:Activity
BFO Occurrent
Ontology alignment using PROV | Simon Cox18 |
ssn:Observation
om:Observation

19. Conclusion
Term “Observation” is being used for different concepts in SSN cf O&M
Record of observation vs. observation event ?
Prov-O helps clarify, without getting
tangled up in formal ‘Upper Ontologies’
Ontology alignment using PROV | Simon Cox19 |
ssn:Observation
om:Observation
new:ActivityOfSensing
om:Process
ssn:Sensor
om:Result
ssn:SensorOutput

20. LAND AND WATER
Thank youCSIRO Land and Water
Simon Cox
Research Scientist
t +61 3 9252 6342
e simon.cox@csiro.au
w www.csiro.au/people/simon.cox

21. The need for standardisation
• Integrated modelling is becoming
the norm
• bioregional assessment
• eReefs
• When using heterogeneous (data)
sources, discovery & integration is a
major challenge
• Standards make this easier
Many private contracts
one public agreement
Ontology alignment using PROV | Simon Cox21 |
Remote sensing
Sensor
Value
Parameter
Scene
Earth science
Algorithm, code,
simulator
Model, field
Variable
Volume, grid
Metrology
Instrument
Value
Measurand
Sample
Chemistry
Instrument,
analytical process
Analysis
Analyte
Sample
Environmental
monitoring
Gauge, sensor
Value, time-series
Parameter
Station
Observations &
Measurements
procedure
result
observed property
feature of interest

22. Views of data
Continuous phenomena, varying in space
and time – ‘raster’.
A function: spatial, temporal or spatio-
temporal domain to attribute range
Ontology alignment using PROV | Simon Cox
Features
Features exist, have attributes and can be
spatially described – ‘discrete’ or ‘vector’
Coverages
Observations
An act that results in the estimation
of the value of a feature property, and
involves application of a specified
procedure, such as a sensor,
instrument, algorithm or process
chain
22 |