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Re: [ontolog-forum] Theoretical issues and practical applications

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rob Akscyn" <ra33@xxxxxxxxxxxxxxxx>
Date: Tue, 5 Jan 2010 19:05:14 +1300 (NZDT)
Message-id: <51020.74.98.253.220.1262671514.squirrel@xxxxxxxxxxxxxxxxxxxxxxxxxx>
John,    (01)

Thanks again for your wonderfully-written notes. I always enjoy reading them.    (02)

***    (03)

With respect to the issue of merging multiple databases and banks never
doing it, I would like to suggest the issue is mainly the cost of mistakes.
If banks do close accounts and reopen them, well .. that sure sounds like
'merging' to me (in this case done manually to ensure few if any mistakes).    (04)

But I think the general issue of merging knowledge bases, or ontologies, 
whatever,
is a genuine issue, especially in research contexts. For instance, I hope to 
see the day
when most digital libraries are merged (say for example, ACM and IEEE). So I 
personally
see high value in exploring this issue further, even if turns out that bankers 
never
make mistakes.    (05)

Sincerely,
     Rob
********************    (06)


> Jim,
>
> Those are very good questions.  As a general comment, I would say
> that there is no one-size-fits-all solution.  And *every* simple
> slogan should be considered highly suspect.
>
> JR> ... this discussion has yet to grapple with the practical
>  > problems arising from the notion that the web will allow us
>  > to integrate lots of knowledge bases to achieve a larger scope
>  > of understanding than would result from any single project.
>  > The intractability of formal reasoning poses a real threat
>  > for this situation.
>
> The first point I'd make is that one of the most pernicious
> slogans is the following:
>
>     Tractability  =  Polynomial time  =  Good.
>
> When you're talking about billions of data items, any polynomial
> with an exponent greater than 1 is a disaster.  A billion squared
> is a quintillion.  And if you could process each data item in
> one microsecond, a quintillion microseconds is greater than
> the age of the universe.
>
> For the web, you need logarithmic, linear, or at worst (N log N)
> algorithms.  That's for the data.  But if you can extract some
> subset of the data by those kinds of algorithms, then you can
> take more time for the items of interest.
>
> As an example, Experian -- one of the three major credit bureaus
> that evaluates everybody's credit rating -- uses Prolog.  In fact,
> they use Prolog so heavily that they bought Prologia, the company
> that was founded by Alain Colmerauer, who implemented the first
> Prolog interpreter.  They keep their algorithms secret, but I
> would guess that they process the raw data in linear time and
> extract smaller numbers of items of interest for more detailed
> processing by more complex reasoning methods.
>
> JR> Where is the research on central control of design and analysis
>  > for logical systems? Where is the work on testing large collections
>  > of knowledge and on determining the testing requirements for
>  > merging two or more knowledge bases?
>
> I'm sure that you remember the work on database schemas from the
> '70s and '80s.  In 1980, there was a workshop that brought together
> three groups:  programming language researchers, database researchers,
> and AI researchers.  Among the participants were Ted Codd, Pat Hayes,
> Jaime Carbonell, Ray Reiter, and quite a few others including me.
>  From the dusty copy of the proceedings in my basement, I would
> draw two sobering observations:
>
>   1. The workshop had only a single track, but the talks clustered
>      in three disjoint mini-workshops:  Prog. languages, DB, and AI.
>
>   2. The topics covered and the level of the discussion was almost
>      indistinguishable from the typical proceedings in ontology
>      conferences today.  If anything, many of the recent conferences
>      have degenerated to RDF & OWL hacking that is at about the same
>      level of sophistication as typical SQL hacking.
>
> To answer your question about when we can expect to merge independent
> knowledge bases, I suspect that the answer is never.  When two banks
> merge, they never merge their databases.  Either they keep both DBs
> operating independently, or they close the accounts from one DB and
> open new accounts in the other.  But banks have been interoperating
> successfully since the Italian Renaissance by passing messages
> (either paper or electronic).
>
> People also interoperate by passing messages.  Except for the
> rather rare Vulcan mind-melds, they never merge their knowledge
> bases.  I doubt that computerized KBs will be merged any more
> easily than banks or people.
>
> Bottom line:  Focus on message processing, not on merging KBs.
>
> John
>
>
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>    (07)



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