Many thanks, Steve.
What I have an issue with is equating the development of a consensus data model with the development of a robust ontology. In a previous email, Rich hoped that DSW might be harmonized with BCO. I really am not sure that is possible and is perhaps not even desirable. DSW and BCO are in my mind apples and oranges.
I agree. Through this discussion, I have since come to see my earlier position as unrealistic and naïve; and, in fact, not even necessarily desirable (as Steve indicates). So no resistance from me on that point.
Although we've called DSW an "ontology" because it's written in OWL and uses some of the constraints present in OWL to restrict how the DSW terms can be used, it really is fundamentally a data model, not an
ontology.
The basis of DSW (outlined at
http://code.google.com/p/darwin-sw/wiki/RelationshipToExistingModels)
was pretty much laid out in Rich's email
http://lists.tdwg.org/pipermail/tdwg-content/2010-October/001703.html
based on the ASC model as modified by the discussion of "individual" in
the 2010 discussion.
The DSW model says that one to many Events can happen at one Location, one to many Occurrences can be documented during one Event, one Individual
can be recorded in one to
many Occurrences, etc. The DSW model does NOT define (ontologically) what
a Location, Event,
Occurrence, or Individual is (other than in the documentary text) or how
they are related to each other
ontologically (except to say that the class instances can be connected
through DSW object properties,
e.g. <dsw:IndividualOrganism instance> dsw:hasOccurrence <dwc:Occurrence
instance>.
DSW is designed to describe (and to some extent restrict) how its users
should organize their data to
allow them to aggregate their data with other DSW users and to allow
queries to be constructed
that will produce consistent results across providers.
Let me just say here that, while I agree with everything you say above (i.e., that DSW is more of a data model with some ontological characteristics, than a proper ontology), I see DSW as an EXTREMELY valuable step in the right direction. Back when Steve first posted all that information to the google code site, we printed up a copy of the diagram at the top of this page: https://code.google.com/p/darwin-sw/ on large-format paper, and it remains posted on the wall in the office that Rob and I share as a guide. We now have our own diagram (which is currently sketched on a whiteboard right next to the DSW diagram), which is conceptually almost identical, but with some extensions and additional features (e.g., many-to-many relationship between Occurrence and "Evidence" (=token); hierarchical Locations, Events, Evidence, and Individuals; etc.).
But like Steve, what we have is a data model, not an ontology.
I think we clearly need a mechanism for defining and clarifying the
relationships
among material samples, organisms, specimens, material entities,
populations,
etc. and BCO or something like it is probably the best way to do that
clearly.
But I don't think that the resulting ontology is going to be a data model
like
DSW or ASC. I think a consensus ontology and a consensus data model would
both be very useful, but I don't think they will or should be expected to be one and the same thing.
OK, I think this is an extremely important point. So, I guess the question is: which should we focus on? Data model, or ontology? The obvious answer is "Both". However, if it is "Both", then the historical trend is that one class of people tend to converge around the ontology, and another class of people tend to converge around the data model (both classes being subclasses of the superclass "biodiversityDataNerd") -- which is sort of the predicament we're in right now. My earlier comment about moving the center of mass of the discussion was an effort to build some bridges between these two currently largely non-connected) conversations.
I have a lot of experience thinking about data models, and a lot to contribute on that topic. I have very little experience thinking about ontologies, and very little to contribute on that topic (my definition of "ontology" is the one Roger Hyam showed at TDWG a few years ago: "Ontology: blah blah blah"). But I also recognize the strong need for these groups to co-mingle more than they have been. We definitely need an ontology to allow reasoning across the information stored in our data models; but it's not unusual for me to see pieces of biodiversity ontologies that could have benefitted from some better insight on how the biodiversity data are modeled (though this may have been limited to early biodiversity ontology efforts -- I haven't kept up lately).
All of this rambling to ask: What do we do next? Do we need to stop talking about DWC and start talking about..... what? Data Modeling? Ontology? Both? Separately? Concurrently? On this list? On a Wiki somewhere...? I really have no idea or opinion about where we go from here -- as long as it's not the same old circular conversation (also, I'd rather it not be "nowhere").
Aloha, Rich