Thanks @clairblacketer . I’ll work on putting something more formal, and ideally further thought out, with a little help from some constructively critical colleagues.
I’m not sure if others agree but I’m advocating that the scope of FACT_RELATIONSHIP should only include relationships that either:
- explicitly and discretely represented in the source data, or
- were created by an established derivation process (e.g. NLP, imaging, episode derivation, etc.), ideally with those records also containing context as to the derivation provenance (e.g. DOI for the algorithm) but I’ll leave the “derivation_id” argument for another thread
In other words, this would exclude any implicit relationships, even when plausible, that could be biased and/or based on fuzzy logic.
@jmethot Wow. That is both hilarious and a little scary as I had no recollection of it, at least consciously. Even funnier is that I appear to provide some opposition but I believe, with a grain of salt as even I have trouble understanding my points, I was pushing back on the idea that the table would serve as a proof of concept that would then generate domain-to-domain specific tables and not opposing the proposed FR structure itself.
But yes, @jmethot , that is nearly identical and a great find. I believe the only delta there would be the focus on the specific subset of domain-to-domain concepts intended to confine valid usage of the approach, but perhaps that was implicit in that proposal as well.
Judging by the end of that thread…
and @Christian_Reich’s infallible memory, perhaps he can enlighten us as well?
As stated above I’ll work on getting this into a more succinct proposal, perhaps with additional focus on the perceived benefits and options for what the concept sets would consist of. In the meantime if folks have any lingering feedback, the more critical the better, I’d love to hear it.