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

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