On Fri, Oct 22, 2010 at 12:03 AM, Cam Webb
<cwebb@oeb.harvard.edu> wrote:
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 : <#> .
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 .
========================================================================
====================== Example 2 =======================================
@prefix oboe: <http://ecoinformatics.org/oboe/oboe.1.0/oboe-core.owl#> .
@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#> .
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" .
========================================================================