This is a debugging problem, but not a deployment problem.
If one's
data is inconsistent one needs to fix it. Usually such
inconsistencies are either errors in the data that need to
be fixed,
or indications that one needs to get clearer about what one
wants to
say. In this case you need to make a choice about whether
you want to
say something that we called in [1] the 'statement level' or
the
'domain level'. If at the domain level you need to put your
neck on
the line and say which experiment is right. If at the
statement level
you need to remodel so that you are clearly communicating
that you
are representing author statements.
-Alan
[1] section 2,3 of http://ow
l-workshop.man.ac.uk/acceptedLong/
submission_26.pdf
On Apr 17, 2007, at 9:53 PM, samwald gmx.at wrote:
>
>
>> I think *if the ontology classifies reasonably at
all*, then this
>> sort of query approach can achieve reasonable
performance for this
>> rough application profile with a reasonable amount
of engineering
>> effort in many cases.
>
> Oh, but this is quite an important
> We can expect that most of the ontologies that are
based on 'real
> data' are inconsistent, if not even highly inconsistent
-- not
> because of errors on the side of the ontology
designers, but
> because the represented information is contradictory.
For example,
> we have found some inconsistency in one of our SenseLab
OWL
> versions that was caused by the fact that the results
of two
> experiments that were entered into the knowledge base
were
> contradictory. Of course, this is a good example for
the utility of
> an OWL reasoner, because it pointed us to a
(potentially
> interesting or important) contradiction in the
literature.
>
> However, such contradictions could lead a
reasoning-based approach
> to querying fail, or at least they can make them less
performant,
> as you said.
>
>
> cheers,
> Matthias Samwald
>
>
>
>
>
> .
> --
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