Re: [ontology-summit] Invitation to a brainstorming call for the 2011 On

[Michael F Uschold <uschold@xxxxxxxxx>]

Ian,

Your points are technically accurate, but miss the social aspect, which is profoundly significant.  Socially, OWL is being pushed as a standard for representing ontologies.  Hence more and more companies are feeling that they should use OWL because there is a perception of more tools, greater support, less vendor-lockin and a larger community.

I recently read through various abstracts in the Linking Enterprise Data book. One chapter caught my attention: Standardizing Legal Content with OWL and RDF.

Kluwer created OWL ontologies for the legal content that is their core business. They got all tied in knots with the open world assumption. I could not help but think that they might have been better off using an FLogic-based approach that is supported by say Ontoprise or HighFleet (formerly Ontology Works).   

The answer is not to harp on OWL, as you say, but to recognize that there are needs for broader support for other approaches.  High FLeet supports Common Logic, and it is a standard - but noone cares about it because noone is using or supporting it. 

It is not so easy to just let the market decide. The market responds to what is available and what is being supported, and what is being actively marketed to them (i.e. OWL and RDF, but not Common Logic or FLogic).

Kluwer likely would have avoided all their open world problems had the battle for OWL been won by the non-DL camp.  They would have used the standard and it would have been closed world.  

Perhaps in 10 years or so, when semantic approaches are more mainstream there will be room for multiple standards that all get major support.

Michael 

On Tue, Dec 14, 2010 at 10:32 PM, Ian Horrocks <ian.horrocks@xxxxxxxxxxxxxxx> wrote:

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 "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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--
Michael Uschold, PhD
   Senior Ontology Consultant, Semantic Arts

   LinkedIn: http://tr.im/limfu
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