O&M Specimen model – alignments with PROV, BCO
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Recent work aligning the Specimen model/ontology from ISO 19156 with PROV and BCO
![Sampling features & specimens
IGSN Metadata workshop - 2015-09-03
«FeatureType»
OM_Observ ation
«FeatureType»
SF_SamplingFeature
+ lineage: LI_Lineage [0..1]
+ parameter: NamedValue [0..*]
constraints
{sampledFeature->forAll(not (oclIsKindOf
(SF_SamplingFeature) or oclIsKindOf
(OM_Observation)))}
SamplingFeatureComplex
+ role: GenericName
«FeatureType»
GFI_Feature
«FeatureType»
SF_SamplingFeatureCollection
Intention
+sampledFeature
1..*
0..*
+relatedSamplingFeature
0..*
Collection
+member 1..*
Design
+relatedObservation 0..*
SF_Specimen
+ currentLocation: Location [0..1]
+ materialClass: GenericName
+ samplingLocation: GM_Object [0..1]
+ samplingMethod: SF_Process [0..1]
+ samplingTime: TM_Object
+ size: Measure [0..1]
+ specimenType: GenericName [0..1]
SF_SamplingFeature
+ lineage: LI_Lineage [0..1]
+ parameter: NamedValue [0..*]
Location
+ geometryLocation: GM_Object
+ nameLocation: EX_GeographicDescription
GFI_Feature
SamplingFeatureComplex
+ role: GenericName
PreparationStep
+ processOperator: CI_ResponsibleParty [0..1]
+ time: TM_Object
SF_Process
+processingDetails
0..*
Intention
+sampledFeature 1..*
0..*
+relatedSamplingFeature
0..*
Cox, OGC Abstract Specification – Topic 20: Observations and Measurements 2.0
ISO 19156:2011 Geographic Information – Observations and measurements](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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O&M Specimen model – alignments with PROV, BCO
- 1. O&M Specimen model – alignments with PROV, BCO Simon Cox | Research Scientist | Environmental Information Infrastructures 3 September 2015 LAND AND WATER
- 2. Sampling features & specimens IGSN Metadata workshop - 2015-09-03 «FeatureType» OM_Observ ation «FeatureType» SF_SamplingFeature + lineage: LI_Lineage [0..1] + parameter: NamedValue [0..*] constraints {sampledFeature->forAll(not (oclIsKindOf (SF_SamplingFeature) or oclIsKindOf (OM_Observation)))} SamplingFeatureComplex + role: GenericName «FeatureType» GFI_Feature «FeatureType» SF_SamplingFeatureCollection Intention +sampledFeature 1..* 0..* +relatedSamplingFeature 0..* Collection +member 1..* Design +relatedObservation 0..* SF_Specimen + currentLocation: Location [0..1] + materialClass: GenericName + samplingLocation: GM_Object [0..1] + samplingMethod: SF_Process [0..1] + samplingTime: TM_Object + size: Measure [0..1] + specimenType: GenericName [0..1] SF_SamplingFeature + lineage: LI_Lineage [0..1] + parameter: NamedValue [0..*] Location + geometryLocation: GM_Object + nameLocation: EX_GeographicDescription GFI_Feature SamplingFeatureComplex + role: GenericName PreparationStep + processOperator: CI_ResponsibleParty [0..1] + time: TM_Object SF_Process +processingDetails 0..* Intention +sampledFeature 1..* 0..* +relatedSamplingFeature 0..* Cox, OGC Abstract Specification – Topic 20: Observations and Measurements 2.0 ISO 19156:2011 Geographic Information – Observations and measurements
- 3. sam-lite ontology IGSN Metadata workshop - 2015-09-03 Cox, SJD, Ontology for observations and sampling features, with alignments to existing models, Semantic Web Journal (in review) http://www.semantic-web-journal.net/content/ontology-observations-and-sampling-features-alignments-existing-models
- 4. Core PROV model IGSN Metadata workshop - 2015-09-03 samfl:Specimen rdfs:subClassOf prov:Entity . samfl:Process rdfs:subClassOf prov:Agent .
- 5. Specimen preparation and observation trace Lifecycle events modelled as prov:Activity instances • Analysis • Sieving • Grinding • Splitting • Specimen retrieval IGSN Metadata workshop - 2015-09-03 Cox, SJD, Car, NJ, PROV and Real Things, MODSIM 2015
- 6. Other alignments and extensions prov:Entity ← :PhysicalEntity ← :Specimen prov:Entity ← prov:Plan ← :SamplingProtocol prov:Agent ← :SampleProcessingSystem ← :GrindingSystem, :PolishingSystem, :DissolvingSystem, :FusingSystem prov:Agent ← :SampleRetrievalSystem ← :FieldSamplingSystem prov:Agent ← :SubSamplingSystem ← :BiasedSplittingSystem ← :SizeSeparationSystem , :DensitySeparationSystem, :MagneticSeparationSystem prov:Agent ← Instrument , Sensor prov:wasAssociatedWith ← :wasControlledBy, :wasSponsoredBy, :wasRequestedBy prov:wasDerivedFrom ← :unbiasedSplitFrom, :biasedSplitFrom prov:wasDerivedFrom ← prov:hadPrimarySource ← :fieldSpecimen IGSN Metadata workshop - 2015-09-03
- 7. Biological Collections Ontology IGSN Metadata workshop - 2015-09-03
- 8. Biological Collections Ontology IGSN Metadata workshop - 2015-09-03 BFO:IndependentContinuant ↔ prov:Entity ← BFO:MaterialEntity ↔ :PhysicalEntity ← BCO:MaterialSample ↔ :Specimen BFO:Process ← prov:Activity observing, sampling, extraction processes
- 9. O&M, OBOE, BCO, BFO alignment • Walls, Jones, Cox, Guralnick, Schildhauer, Buttigieg – coming soon! IGSN Metadata workshop - 2015-09-03
- 10. 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
Hinweis der Redaktion
- In order for the vision of the semantic web to be fulfilled, ontologies developed for related applications and deployed by different organizations must be aligned. Some ontologies are tied to a particular foundation ontology (such as BFO, GFO, UFO or DOLCE) by design, with their key classes in a subsumption hierarchy derived from the upper ontology. This enables rapid alignment with other ontologies developed in the same framework, but can present barriers otherwise. The Semantic Sensor Network ontology (SSN) was developed through a W3C incubator group with the goal of providing a general purpose ontology for sensor-based observations. It has seen widespread adoption in the semantic web community. On the other hand, in the geospatial community, OGC Observations and Measurements (O&M) provides the model used for standard observation services. While SSN adopts much of the terminology from O&M, full alignment has been a challenge. This is confounded by the fact that each is rooted in a different base “ontology” – SSN uses DOLCE as its foundation, while O&M is formalized as part of the ISO/TC 211 harmonised (UML) model. While some conflict derives from the tension between the frame-based UML paradigm used for O&M and the open-world, description-logics based paradigm used in SSN, this does not appear to be the whole story. A possible resolution is provided by comparing recent studies that align SSN and O&M, respectively, with the PROV-O ontology. PROV-O provides just three base classes: Entity, Activity and Agent. om:Observation is sub-classed from prov:Activity, while ssn:Observation is sub-classed from prov:Entity. This implies that, despite the same name, om:Observation and ssn:Observation denote different aspects of the observation process: the observation event, and the record of the observation event, respectively. Alignment with the simple PROV-O classes has clarified this issue in a way that had previously proved difficult to resolve. The simple 3-class base model from PROV appears to provide just enough logic to serve as a lightweight upper ontology.