US-VO Semantics: from Bertram Ludasher

[Carole Goble]

Bertram wrote in his discussion:

> If you need real *reasoning* capabilities, i.e., given a definition of

> a concept A and another definition of a concept B, does one contain or

> exclude the other (or are they equivalent), then you need to look at
> "Description Logics". Probably you do not need this functionality, but

> I just mention it for completeness.

I find this extremely strange as a comment.   Bertram suggests that
there are the "before semantic web" and "after the semantic web"
languages. This is not true.  OWL (see point (b)) is heavily influenced
by Frame-logic work by Karlesruhe. RuleML (see (c) ) is linking Datalog
and Horn Logic with DAML+OIL.  To be so dismissive doesn't do you
justice Bertram!!

(a) The classification based reasoning that DLs give you is EXACTLY the
kind required to build controlled vocabularies. Controlled vocabularies
for content will be the primary use of ontologies in this field I
suspect as they are in biology.  we are using DAML+OIL to rebuild the
Gene Ontology, and I cantell you we aren't doing it for our health. We
are doing it because "we DO need this kind of functionality" to build
large, multi-axial, coordinated and multi-authored ontologies.
Subsumption based reasoning, and its associated query inclusion and
indexing is highly valuable, not to mention the axioms for ensuring
concept satisfaction. I'll put a couple of papers about our experiences
on this on a web site -- they are in press so I have to seek permission
to do so. We have also used these approach in myGrid for describing and
matching services (http://mygrid.man.ac.uk/rpapers.shtml), as have HP
(see http://www2002.org/CDROM/refereed/211/index.html)
All of this is reasoning with *intension*.

If you are arguing about inference over instances with variable, then
that is another argument.  *extensional* reasoning is better served by
conventional database languages and even deductive databases,

For controlled vocabularies Deductive Databases seem like an overkill --
this goes back to your point about "what do you want to do with your
representation".  In fact, DD for ontological reasoning is probably
missing the point.

b) DAML+OIL and OWL (the language that has derived from DAML+OIL,
proposed by W3C WebOnt and now released in draft form) does have the
benefit of a community of tool builders producing parsers, editors,
matching engines, viewers, annotators etc etc.  This should not be
underestimated.  It also gives you a range of reasoning engines, if you
want that sort of thing, or just a common exchange language if you want
that sort of thing too.
I recommend that you take a look at the OWL spec:
http://www.w3.org/2001/sw/WebOnt/
By the way, OWL-Lite is (I believe) supportable by F-Logic reasoners as
well as conventional DL reasoners.

c) The use of Datalog style reasoning with deductive rules is useful, of
course, in particular if one wants to do process modelling and planning
& scheduling  work. Attempts are being made in the Semantic Web world to
incorporate DAML+OIL terms in rule languages. An interesting place to
look at is RuleML  activity:
http://www.dfki.uni-kl.de/ruleml/         I haven't used FLORID in a
long time but I do remember problems with robustness and legacy data,
and wasn't it undecidable as well as intractable?  Tractability is only
obtainable in DD by the Closed World Assumption.  Again, CWA can be
presumed over querying instances, but reasoning about possibilities, as
one would want to to do ontological intensional reasoning, is best
served by the open world assumption.

d) RDF, though a simple graph model, is weak but it is promising for
data integration and does have some reasoning capabilities. The point of
RDF as a graph model is really to support data aggregration through
graph matching --  in the way that TAP does for example
(http://tap.stanford.edu/). You shouldn't lose sight of the fact that
the Semantic Web movement if actually about DATA INTEGRATION and not
about AI at all. This sometimes gets forgotten :-)

e) One of the import things you should not lose sight of is the
"semantic continuum" (trademark Mike Uschold). By this I mean that some
of your ontologies will be no more that simple hierarchies, and some
will need subsumption reasoning. And some will want other forms of
reasoning that take them out of the decidability camp.  Moreover, you
will want to slide along this continuum --starting simple and then
selectively elaborating. Or even going the other way and selectively
simplifying. Have a language that allows you to say as little or as much
as you want in the same framework, and provides reasoning support for
evolution, is darn handy. That is why we use DAML+OIL.

f) Finally -- take care about ontology development vs ontology
deployment. You could use all sort of fancy stuff in design (and I would
argue that it is needed - see (a) ) but then generate a simple
representation for deployment -- say in RDF, or even Topic Maps.  You
cannot assume in the Grid or the Web that your deductive database or
your reasoning engine is available, but you still want to get something
out of your metadata.

Conclusion -- there is no one technology, we need a basket of
technologies working in consort that do the best job for what you need.

Carole