The following question(s) were asked in the Collection Management Systems Webinar and will be answered here.
Francesca Jaroszynska: how can the entityRelationship table handle partial information when the entity observation is a collection of individuals of a given taxon? Could nesting observations in the Entity table be more efficient? For example, when information on lifeStage, sex or ID tags are available for only some of the individuals observed.
This is an interesting question whose solution could also apply to lots in collections where individuals are not identified or tracked separately, but subsets of which do have distinct attributes. An example is the best way to demonstrate one way to deal with this.
Let the scenario be a monitoring Event targeting a flock of pigeons at a particular city site. One of the pigeons has a band and so can be identified as a specific individual with known sex and life stage. The goal is to do as well as possible characterizing the population structure in terms of sex and life stage.
First we need the Event:
The Entities that can be instantiated are the pigeon population “PigeonPopulation1”, and the marked pigeon “Pigeon1”, which is a member of that population. Both are dwc:Organisms, though one has a dwc:organismScope of “population” and the other has a dwc:organismScope of an “individual”.
To capture the scope of the Organisms we can use EntityAssertions:
In order to connect the Entities with the monitoring event in which they were observed, we need EntityEvents, one for the population:
and one for the marked individual:
We need to show that “Pigeon1” was a part of “PigeonPopulation1” on the date observed. We’ll do that with an EntityRelationship:
entityRelationshipType: member of
The property entityRelationshipDate is not yet in the Unified Model yet, but this mini use case highlights the need for it. The complementary EntityRelationship is:
entityRelationshipType: has member
Now we can model the attributes of “Pigeon1” with EntityAssertions. Let’s say the marked pigeon is an adult female:
Now we can model the attributes of “PigeonPopulation1”, also with EntityAssertions. The flock had 13 individuals on the day they were observed, including the banded individual:
It was easy enough to distinguish the juveniles from the adults:
entityAssertionType: juvenile count
entityAssertionType: adult count
But the sex of the adults could only be divined by their behavior, which 4 of the unmarked adult population exhibited:
entityAssertionType: minimum adult male count
entityAssertionRemark: determined by behavior
entityAssertionType: minimum adult female count
entityAssertionRemark: determined by behavior for two individuals, the third was a marked individual of confirmed sex