Hi Ian, (01)
On 12/15/2010 11:42 AM, Ian Horrocks wrote:
> [re-posted here as per request from Peter]
> I'm constantly amazed at the passion that OWL seems to arouse. 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.
> 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
Thank you, as always, for calmness and perspective. (03)
The Manchester syntax should (hopefully) put to rest assertions
about XML or any other serialization of OWL. The OWL 2 profiles
and metamodeling additions also did much to address earlier concerns. (04)
Adults and those with business interests will make their own
choices as to what frameworks they employ. I, personally, do not
need to be told over and over again how all of this OWL and
semWeb stuff sucks. I think as Jim Hendler stated some years
back, "a little semantics goes a long way." (05)
For the reasons you state, OWL has its place and role; in other
respects, other frameworks do as well. Structured Dynamics has
chosen to (attempt to) bridge both the Cyc and semantic Web (OWL)
worlds with UMBEL. It is doable. (06)
For one, I very much appreciate your grace in continuing to
engage this forum. (I wish I could assert the reciprocal.) And,
we (SD) really appreciate your dedicated work to bring us
responsive and workable frameworks. (07)
I tip a glass to you this Holiday Season! (08)
Best wishes, Mike (09)
> On 10 Dec 2010, at 10:57, John F. Sowa wrote:
>> 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:
>> 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".
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Michael K. Bergman
CEO Structured Dynamics LLC
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