Re: Pizza Example

From: Chris Hoess <>
Date: Sun, 18 Apr 2004 07:33:09 +0000 (UTC)
Message-ID: <>

In article <>, Anthony W. Youngman wrote:
> In message <>, Chris Hoess

><> writes
>>I'm not sure asking for "scientific" proof of something that's not a
>>scientific theory makes sense. Newtownian mechanics offers rules by which we
>>can describe the world. The relational model offers rules for the
>>manipulation of propositions, whose mapping to the real world is arbitrary
>>(but should be consistent for each individual database). I suppose I might
>>try to put the premises of the relational model thus:

> I know what you're saying. But that is confirming that relational theory
> is a branch of *pure* mathematics. As such, you are admitting that you
> have no evidence that it has any relationship whatsoever with the real
> world - and if that is the case what on earth is the point of trying to
> model the real world using it?!

Nonsense! Consider the equation for a Gaussian distribution. In and of itself, it has no connection with the real world; it's only an arrangement of arbitrary parameters and variables. Only by inserting meaningful properties into this equation are we able to tie its results to the real world, at which point it becomes very interesting and useful indeed.  

> I've got no problems admitting that relational is very good, consistent
> model. Where I *do* have a problem is the belief by so many people that
> it is the right model for the real world. And proving that lies in the
> realms of *science*, not maths. (Yes, the dividing line between "applied
> maths" and "experimental science" is very blurred, but until you can
> convince me that there is more to relational theory than Pure Maths,
> I'll continue asking for evidence as to relational's relevance to the
> real world.)

The proof of the pudding is in the eating. As I laid out below, the essential assumptions needed to bridge the gap between the relational model and reality are that you can represent all the information you wish to store as statements, whose plausibility may be evaluated in terms of constraints of first-order logic. The return for this is the consistency, etc. of the relational model.


>>So statements in a relational database are guaranteed to be true to the
>>degree that truth can be defined by the constraints expressed in the


> Substitute "truth" with "consistency". If, by "truth", you mean
> "corresponds with reality", then (a) you can NOT do it automatically,
> and (b) logic is completely the wrong tool - after all didn't Aristotle
> prove that a pound of lead is heavier than a pound of feathers :-) (yes,
> I know I've quoted the story wrong - it was something about falling
> faster or something :-)

Well, it corresponds with reality insofar as the constraints in the database represent those of reality, and the divergence between the two may be very significant. But if you think logic is the wrong tool, then the issue goes far deeper than the relational model versus the "PICK model" versus whatever Neo peddles; computers aren't very good at doing things other than logic, so if you throw that out the window, we're pretty much back to flat files.

>>I am neither by training nor practice a logician, so I'm not entirely sure
>>this description is correct, but I think it's a good starting point for
>>discussion of the issue.

> By training I'm a scientist. Logic is a wonderful tool, but it should be
> tested by experiment ...

But I think we're trying to test things at the wrong level. By taking sufficiently careful measurements and running them through Newtownian mechanics and relativity, relativity should yield a result closer to the measured values than Newtonian mechanics. I don't see how one would be able to carry out a similar comparison with two database models (although I suppose such a test does impose stringent requirements for consistency, which may not be true of all of the half-baked stuff put forth). Dawn's efforts to put this on a scientific footing, while interesting, are mired in a swamp of confounding variables; much more like epidemiology, say, than physics.

Chris Hoess
Received on Sun Apr 18 2004 - 09:33:09 CEST

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