Determining the "Correctness" of a data model

LinkedIn, Data modeling, 2020/3/26
I asked: How do we know when a data model is correct?
Ken Evans responded: That's easy, when the model conforms to stated requirements.
I then asked "who determines/documents the requirements?"
Ken responded:
It does not matter "who" determines the requirements. The point is that you can only judge whether a deliverable is "correct" if you have a set of pre-established requirements against which to assess "correctness". This principle has been widely accepted in the quality management discipline since 1978 when Philip Crosby published his book "Quality is Free." Crosby makes the point that "Quality is conformance to requirements."

Everest Responds:

Sorry about the "who", perhaps I should have said "how." While I accept the general principle, is it realistic? Crosby's statement begs the question, if quality is conformance to requirements, then who/how do we determine the correctness and completeness of the stated requirements? I have yet to see anything close to an a priori statement of requirements that was sufficient to judge the correctness of the end result, i.e., a domain data model. Furthermore, I have yet to see any guidelines sufficient for preparing a statement of requirements for a data modeling project. I would love to see any examples.

.. To me, the only satisfactory "statement of requirements" sufficient to judge the correctness of the model would be the final, detailed data model itself. Anything less than that would not be sufficient to express the full set of semantics to be included in the final model. In the case of ORM perhaps, a complete set of elementary fact sentences, with well defined object types and predicates. But that is what the entire process of data modeling is all about -- to discover and document the semantics of some user domain. We want to capture at least as rich a set of semantics as possible given our modeling scheme (which is why we need to use a modeling scheme such as ORM which captures many more semantics than any other scheme, including ER/relational).

.. So the question remains, whether we are talking about the data model, or the requirements for a data model -- how do we judge the correctness of a data model? Who is in the best position to do that?