ONT RE: Ontology case study
John, Adam, et al.,
I am (still) trying to understand when and why one would use an ontology
versus a data model for a given goal, such as answering queries. There are
probably many answers; I'm just looking for some that I can understand.
John said, in part, ...
<snip>
JS: > Although I agree with Matthew's claims for data models, I would like
> to point out that there is no difference in principle between data
> models and ontologies. Following are the correspondences:
>
> 1. Both have types and relations (AKA predicates), which are or
> can be organized in a hierarchy of types and subtypes.
>
> 2. Both require definitions, although the DBMS models usually use
> some less rigorous language, such as English. But as I have
> insisted for a very long time, the definitions should be in a
> structured, stylized, or controlled English (or other natural
> language) that has a direct mapping to logic. If we used such
> languages, the difference in appearance between the DB and AI
> definitions would disappear.
>
> 3. There is no difference in principle between the DB constraints
> and the AI axioms. In fact, the DB constraints, which are usually
> stated in SQL can be translated directly (even automatically)
> to any common notation for FOL, such as KIF, CGs, or, what I would
> recommend, controlled English.
JF: Even though you see no difference in principle between DB constraints
and AI axioms, mightn't it still be the case that in practice there are
certain kinds of axioms that AI folk typically use in an ontology that DB
folk don't use in a data model? If so, could you give some examples?
JF: If this isn't the case (i.e., if there is no difference in practice
between the kinds of constraints found in DB-land and the kinds of axioms found
in AI-ontology-land) then don't we need to ask something like "Why use an
ontology?"
Matthew responded to another email on a different thread saying:
MW: I think it is just horses for courses. Data models grew up to support
database design. It is not surprising that they are quite good if that
is what you are doing.
I'm thinking, "OK. So data models are good for database design. And
ontologies, then, are good for ...??"
One reason to design and build a database is use it to answer questions.
Is the SUO group building ontologies, in part, to answer questions?
If so, are the questions to be asked and answered of a different kind
from those that can be put to and answered by a DBMS?
Or, perhaps, because ontologies deal with different kinds of subject
matter, the mechanisms that "ontology systems" use to answer questions are
not typically found in commercial DBMS (and hence this is why we
need an ontology system and not a database system)?
Maybe Adam could also chime in on why he feels that the
case study he mentioned used an ontology not a data model. I will study
again the correspondence between Matthew and Adam on that, but I am wondering
if Adam might be able to collect his points into a short list?
Thanks,
Jim