[tdwg-content] practical details of recording a determination What is an Occurrence?

[Cam Webb]

Hi Kevin,

> I can't help but feel we are getting into a much more complicated area 
> of biodiversity ( or any observation oriented field for that matter ) 
> and that there must be other ontologies or models that we could follow 
> or reuse.

If you are referring specifically to adding depth to the observations of 
Individuals, I think one might look first at OBOE (OBOE: Extensible 
Observation Ontology) from the SEEK group at NCEAS:

   http://ecoinformatics.org/oboe/oboe.1.0/oboe.owl

In summary, this describes an Observation of an Entity, with the 
Observation comprising a Measurement of the Value for a Characteristic of 
the Entity:


@prefix oboe: <http://ecoinformatics.org/oboe/oboe.1.0/oboe-core.owl#> .

[]  a oboe:Observation ;
     oboe:ofEntity [
         a oboe:Entity ;
         ] ;
     oboe:hasMeasurement [
         a oboe:Measurement ;
         oboe:ofCharacteristic [
             a oboe:Characteristic ;
             ] ;
         oboe:hasValue [
             a oboe:Entity ;
             ] ;
         ] .


If we assert that a dwc:Occurrence is an instance of oboe:Entity, with 
dwc:basisOfRecord of "HumanObservation", with a dc:creator and dc:created 
(i.e., the space-time intersection of an Individual and a human observer), 
we can marry these two ontologies quite nicely.  Please see Example 1, 
below, for a description of the fruit color of an individual plant.

What's nice about the OBOE model is that it contains all three possible 
parts of an observation: the entity, the characteristic and the value. 
This allows direct mapping to the Prometheus Description Model (structure 
+ property + state = entity + characteristic + value; Pullan et al. 2005, 
Taxon 54:751-765), and indirect mapping to the popular EQ model (entity + 
quality, where quality = characteristic + value; Mabee et al. 2007, 
doi:10.1016/j.tree.2007.03.013). However, it doesn't map easily to the 
DELTA or SDD data models (character + character-state, where character = 
entity + characteristic and character-state = value).

Because of the well-developed OBO ontologies, we can directly employ terms 
from, say, the Plant Ontology (po), for an oboe:Entity, and terms from 
PATO, the quality ontology, for a oboe:Measurement, combining 
characteristic and value into a quality.  We need to assert that a 
pato:quality is equivalent to a oboe:Measurement and possibly that a 
po:PO_0000001 (top level `plant structure') is an oboe:Entity.  We can 
also employ the OBO relational ontology (ro) to indicate that a fruit is 
ro:part_of the particular space-time Occurrence of an Individual (this 
might require a bit more discussion!).

So, it seems that using only well-established vocabularies, we can make 
semantic statements about the characteristics of individuals originally 
defined primarily using DwC terms.  Please see example 2, below for a 
fairly slim, usable model of a description of the fruit color of an 
individual plant.  The image of the model is at:

   http://phylodiversity.net/cwebb/img/tdwg-obs.jpg


Again, any comments on this model will be much appreciated.  Are you aware 
of other attempts to join DwC Occurrence models with OBOE models?

Best,

Cam



====================== Example 1 =======================================

@prefix oboe: <http://ecoinformatics.org/oboe/oboe.1.0/oboe-core.owl#> .
@prefix dwc: <http://rs.tdwg.org/dwc/terms/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix sernec: <http://bioimages.vanderbilt.edu/rdf/terms#> .
@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
@prefix : <#> .

<http://phylodiversity.net/xmalesia/indiv/9>
     a sernec:Individual ;
     sernec:derivativeOccurrence _:blank1 .

_:blank1
     # The Occurrence of the Individual...
     a dwc:Occurrence ;
     # ... at a position in space-time...
     dcterms:created "2008-01-01" ;
     dcterms:spatial [
         a dcterms:Location ;
         geo:lon "109.95371" ;
         geo:lat "-1.25530" ;
         dwc:coordinateUncertaintyInMeters "100" ;
         ] ;
     # is a recordable OBOE Entity
 	a oboe:Entity ;
     # as recorded by a human
     dcterms:creator "Cam Webb" ;
     dwc:basisOfRecord "HumanObservation" .

# The details of the observation:
[]  a oboe:Observation ;
     oboe:ofEntity [
         # The observed entity is actually *part of* the occurrence
         #   of the Individual at a particular Space and Time
         a :Fruit ;
         :partOf _:blank1 ;
         ] ;
     oboe:hasMeasurement [
         oboe:ofCharacteristic :Color ;
         oboe:hasValue :Green ;
         ] .

:Fruit a oboe:Entity .
:Color a oboe:Characteristic .
:Green a oboe:Entity .

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====================== Example 2 =======================================

@prefix oboe: <http://ecoinformatics.org/oboe/oboe.1.0/oboe-core.owl#> .
@prefix dwc: <http://rs.tdwg.org/dwc/terms/> .
@prefix dcterms: <http://purl.org/dc/terms/> .
@prefix sernec: <http://bioimages.vanderbilt.edu/rdf/terms#> .
@prefix geo: <http://www.w3.org/2003/01/geo/wgs84_pos#> .
@prefix ro: <http://www.obofoundry.org/ro/ro.owl#> .
@prefix pato: <http://purl.org/obo/owl/PATO#> .
@prefix po: <http://purl.org/obo/owl/PO#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .

<http://phylodiversity.net/xmalesia/indiv/9>
     sernec:derivativeOccurrence _:blank1 .

_:blank1
     a dwc:Occurrence ;
     dcterms:created "2008-01-01" ;
     dcterms:spatial [
         geo:lon "109.95371" ;
         geo:lat "-1.25530" ;
         dwc:coordinateUncertaintyInMeters "100" ;
         ] ;
     dcterms:creator "Cam Webb" ;
     dwc:basisOfRecord "HumanObservation" .

# The details of the observation:
[]  a oboe:Observation ;
     oboe:ofEntity [
         ro:part_of _:blank1 ;
         a po:PO_0009001 ; # Fruit
         ] ;
     oboe:hasMeasurement pato:PATO_0000320 . # Green color

po:PO_0009001 rdfs:label "fruit" . 
pato:PATO_0000320 rdfs:label "green" .

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