[reposted here as requested by Peter] (01)
Dear Ian, (02)
> I'm constantly amazed at the passion that OWL seems to arouse. (03)
I am surprised at the strength and vigour of John's objections too, but I
think you are missing some of what is objected to. (04)
> OWL and the OWL
> 2 profiles are simply fragments of FOL with useful computational
properties.
> I'm surprised that we can get so excited about decidable fragments. I'm
even
> more surprised that someone who apparently likes FOL "hates" these
particular
> fragments. (05)
MW: Well if OWL was just an abstract syntax for these fragments I doubt if
anyone would be half as excited. What I think causes a collective groan
amongst those that have been around for several decades in this space is the
XML implementation on top of RDF. It is like inventing a square wheel when
you have a round one sitting in the corner (SQL) and then layering something
uncomfortably on top of it. (06)
Regards (07)
Matthew West
Information Junction
Tel: +44 560 302 3685
Mobile: +44 750 3385279
matthew.west@xxxxxxxxxxxxxxxxxxxxxxxxx
http://www.informationjunction.co.uk/
http://www.matthew-west.org.uk/ (08)
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>
> I can easily understand why you and others might believe that OWL is too
> restricted for what you want to do, and why you might want to use full
FOL.
> Please go right ahead -- I won't be in the least offended. I don't see how
OWL
> would interfere with such an endeavour, and I would have thought that it
might
> even help as you can trivially extend OWL ontologies with arbitrary FO
axioms.
> In fact, you could think of OWL as being a design pattern, which you
> apparently like, as opposed to a fragment, which you don't like.
>
> Regarding the other techniques you mention, it is true that they can be
used
> to address some of the problems associated with computational complexity
> (where we can think of semi-decidability as being a very high complexity
> class). Modern OWL reasoners already employ many of these techniques. Of
> course we can, by definition, never "deal with" these problems, and
ontology
> languages with high computational complexity will always suffer from some
lack
> of robustness, i.e., relatively small changes in the ontology and/or data
may
> result in performance "falling off a cliff". This was the motivation for
the
> definition of the various OWl profiles: if a given application requires
some
> guarantee of robustness, then they can obtain it by staying within a
suitable
> profile. Note that the syntactic definition of profiles is crucial here,
> otherwise one risks deciding membership of the profile being an
intractable
> problem in itself.
>
> Coming back to the OWL -v- FOL question, I think that much of the
"problem"
> arises from fundamental differences in how we view the design and use of
> ontologies. Many of the ontologies I see are extremely simple (in fact I
often
> find myself being asked to defend the unnecessary expressive power of OWL)
and
> perhaps wouldn't pass muster if examined by a formal ontologist. However,
they
> may still be found to be an extremely useful piece of an application, even
if
> only a rather small piece. I tend to see this in a positive light -- we
are
> raising the profile of and exploring applications for ontologies.
Hopefully
> you can try to see OWL in a similar light -- it is raising the profile of
> ontologies, encouraging the use of (a fragment of) FOL as an ontology
> language, and providing you with a ready source of "customers" ripe for
> "upgrading".
>
> Regards,
> Ian
>
>
>
>
>
> On 10 Dec 2010, at 10:57, John F. Sowa wrote:
>
> > Ian,
> >
> > Before saying anything else, let me emphasize that I believe the work
> > on algorithms, complexity, and decidability by you and your colleagues
> > is very high quality and very important for computer science.
> >
> > But the sentences at the end of your note explain why *I hate OWL* :
> >
> >> In fact, it can be shown that query answering in OWL 2 RL [Rule
Language]
> >> is possible in time that in the worst case increases only polynomially
> >> with the size of the data. In *this* sense, OWL 2 RL really is less
> >> (computationally) complex. However, as I mentioned above, the price
> >> users pay for this is an *increase* in syntactic or cognitive
complexity.
> >
> > By syntactic complexity, I realize that you are talking about something
> > much more fundamental (and cognitively much harder for people to learn)
> > than the angle brackets. But knowledge acquisition has always been
> > the major bottleneck in AI and the SW. Anything that increases the
> > "cognitive complexity" is a bad step in the wrong direction.
> >
> > As Dean said,
> >
> >> I find that in the classes I do teach, the students are very concerned
> >> about complexity in the computational sense...
> >
> > But there are many ways of dealing with computational complexity while
> > actually *reducing* the cognitive complexity:
> >
> > 1. Design patterns. Every programming language is undecidable, but no
> > programmer would ever ask for less expressive power. Instead, they
> > have developed *design patterns* for systematic ways of using their
> > languages in ways that are known to be safe and efficient.
> >
> > 2. Hybrid systems. The original DLs were packaged as hybrids with
> > the DL component designed for efficient classification and a more
> > expressive language (rule-based, full FOL, or even arbitrary
> > procedures) were used to achieve the required expressive power.
> > And design patterns (or something similar) can be used for the
> > more expressive part of the hybrid. (The RL option of OWL doesn't
> > address the main reason why people use hybrids: they need more
> > expressive power, not less.)
> >
> > 3. Dynamic algorithm selection. Cyc has developed the largest formal
> > ontology on the planet, but CycL imposes no restrictions on the
> > expressive power. Instead, they use dynamic methods for selecting
> > appropriate algorithm(s) for each problem or subproblem they
> > encounter. Similar strategies are also used for the systems that
> > compete on the Thousands of Problems for Theorem Provers (tptp.org).
> >
> > 4. Knowledge compilers. For many applications, it's possible to do
> > a *static* selection of the algorithms: Map the very expressive
> > languages (such as CycL and others) via appropriate design patterns
> > to forms can be processed efficiently by known algorithms.
> >
> > I'm sure that you know the references for these methods, but for
> > other readers, I include some in the following article:
> >
> > http://www.jfsowa.com/pubs/fflogic.pdf
> > Fads and Fallacies About Logic
> >
> > At the ICCS 2010 conference, Boris Motik gave a good presentation
> > about adding finite graph models to OWL in order to broaden its
> > expressive power while preserving decidability.
> >
> > I certainly like the idea of supporting graphs, but not the idea
> > of adding more cognitive complexity to an already overstuffed
> > language. Instead of stuffing more into OWL, why don't you ask
> > some of your students to do research on methods such as #1 to #4
> > above to find ways of *reducing* the cognitive complexity?
> >
> > Other talks at ICCS described more efficient algorithms for
> > Formal Concept Analysis (FCA), which generates consistent lattices
> > from source data that is cognitively extremely simple.
> >
> > That would be another excellent topic for your students: design
> > hybrid systems that combine an FCA-style of hierarchy with automated
> > or semi-automated methods for supporting additional expressive power
> > at varying levels of complexity up to the level of CycL.
> >
> > Cognitive complexity is killing the Semantic Web. As a result,
> > people are building their own hybrids that add very scruffy methods
> > to OWL or RDFS or RDFa -- thereby destroying the decidability that
> > the OWL restrictions were designed to support.
> >
> > The four techniques above (or something similar) would be an
> > excellent way to support Tim B-L's project for "Web Science".
> >
> > John
> >
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