Hi Brian,
> I apologize, and then move that we change to a compatible term which
> implies "machine-to-machine" instead (vocabulary? dictionary?)
We're making a habit of agreeing now. Be on the lookout for a red heifer.
> [NLQ] is just far, far away and not as pressing as the issues of
> dataset labeling, machine to machine interchange and development of
> machine understanding of data (e.g. ontologies).
Just as I think "vocabulary" is a better word choice than "thesaurus", so "machine understanding" will be infinitely more comprehensible to laypersons than "ontology". However, is that an "e.g." or an "i.e."? The implication here is that other techniques of machine understanding are possible, broader than the "O" word. If that is the case, isn't this broader topic the true scope of this working group? This might neatly resolve the recurring "ontology" versus "vocabulary" versus "ucd" battles.