Re: what are keys and surrogates?
Date: Thu, 10 Jan 2008 08:05:59 GMT
Message-ID: <Hlkhj.5962$xA6.1492_at_trndny09>
"David BL" <davidbl_at_iinet.net.au> wrote in message
news:e6ba98c3-bc53-45a6-87c6-ea11e8c88616_at_p69g2000hsa.googlegroups.com...
> On Jan 10, 1:22 am, Marshall <marshall.spi..._at_gmail.com> wrote:
> > On Jan 9, 8:07 am, David BL <davi..._at_iinet.net.au> wrote:
> >
> > > On Jan 9, 1:25 pm, Marshall <marshall.spi..._at_gmail.com> wrote:
> >
> > > > This issue goes away if we relax 1NF and allow attributes that are
> > > > lists or relations. This gives us nested structures. (Nested
relations
> > > > are not particularly controversial around here.)
> >
> > > In addition to my previous post, I wish to add another comment
> > > regarding my suspicion with RVAs. The tuples of a relation are
> > > supposed to represent facts, but what does it mean when a relation
> > > merely represents a value?
> >
> > The question is meaningless. The distinction you are drawing
> > does not exist.
>
> In what sense do tuples of an RVA represent propositions in *the* UoD?
>
> > > Isn't the RM meant to have some close
> > > association with FOPL?
> >
> > Yes.
> >
> > > It seems to me there is a fundamental difference between
> >
> > > a) a large collection of propositions relevant to a particular UoD;
> > > and
> >
> > > b) a composite data structure such as an AST which simply
> > > "is what it is"
> >
> > This is an illusion. There is no difference.
>
> Hmmm. Unfortunately you didn't respond to my last paragraph which was
> more tangible.
>
> I don't believe the distinction is an illusion. I'll have a go at
> providing an objective measure on a given relational database d...
>
> Let B(d) equal some measure of the amount of information in d,
> quantified as the total number of bits required to store all the data
> (accounting for "compressibility").
>
Off topic.
I prefer quantified as the difference in entropy between the state that
includes d and the state that excludes it. I believe that, except for a
scale factor, the two measure boil down to the same thing, except for one
subtle difference:
Using entropy as the measure enables one to consider information content as
being context sensitive. That is, if d is to be included in some other