Thanks John, I meant to ask what you thought of my way of using the KR
lattice. It seemed to me a good common sense place to start, and more
sensible than what I sometimes call the "Pizza approach" (Pizza is a
Thing, Base is a Thing, Topping is a Thing), if you are going to model a
complex realm such as business. I think it's particularly important in
financial services because most of our processes cross so many
organisational boundaries and it's important to have precision of what
the real things are. Also the Continuant v Occurrent dichotomy gives you
a way to model processes within an ontology, and these are intimately
tied in to many facts about financial securities. (01)
This is why I felt this could also be a good basis for bringing together
mid-level ontologies of established, industry-standards based terms. (02)
I did struggle with trying to figure out if parts, sets and so on needed
to be fitted into the same lattice or dealt with differently. I'll have
a look at the FCA link, it looks like something I can learn from. Many
thanks for the link. (03)
Best regards, (04)
Mike (05)
John F. Sowa wrote:
> Pat, Ed, Azamat, Dick, and Mike,
>
> PC> After all these years of talking about standard ontologies,
> > I have arrived at the feeling that an ontology is more complex
> > and of a different character than most standards that have been
> > formalized. The detailed means of applying ontologies to practical
> > applications appear to me to be a lot less easy to envision than
> > for most standards. For that reason I think that no ontology
> > should be a formal 'standard' until it has had a lot of public
> > vetting in more than a few applications of the kind it is intended
> > to support.
>
> I strongly agree.
>
> EB> ... the purpose of an ISO "study period" is to determine whether
> > there is a specification or parts of a specification that has
> > sufficient consensus for standardization and meets some perceived
> > communal need (either in industry, or in the making of other
> > standards).
>
> That is a laudable aim. But those terms 'specification' and 'parts
> of a specification' are very unclear by themselves. When it comes
> to ontologies, people tend to focus on the names of the categories
> and their placement in some hierarchy. But pioneers in the field,
> such as Aristotle, Leibniz, and Kant, emphasized the *methodology*
> for deriving the categories.
>
> Aristotle's methodology was to associate a question with each of
> his ten categories. Each subtype of substance is the answer to
> "What is it?" For Quality, "What kind?" For Quantity, "How much?"
>
> Leibniz's methodology was to define his categories as conjunctions
> of primitive features. Then he assigned prime numbers to each of
> his features. The universal category, Entity, had no distinguishing
> features, and its number was 1. All other categories were assigned
> the product of the primes for each of their features.
>
> Leibniz's goal was to replace philosophical disputes with calculation.
> If the number for category A divides the number for B, then A is
> a supertype of B. The result of Leibniz's methodology is a lattice
> with all possible combinations of the features.
>
> Kant's methodology borrowed some aspects from both Aristotle and
> Leibniz. I won't go into the details, but he formed a table of
> twelve types of judgments, each of which corresponded to one of
> his twelve top-level categories.
>
> EB> The idea that some amalgam of BFO, DOLCE and SUO would have
> > such consensus would be supported by findings from the study
> > period that some useful common set of concepts is essentially
> > identical across these ontologies, differing only in terminology.
>
> Two points in that comment seem arbitrary: the phrase 'some amalgam'
> and the choice of BFO, DOLCE, and SUO. As I said before, Cyc is the
> largest formal ontology on planet earth, and it has undergone almost
> a quarter century of continuous development with contributions from
> many highly respected logicians, linguists, philosophers, and experts
> in artificial intelligence.
>
> Almost everybody (including me) has found many aspects of Cyc that
> can be criticized. BFO, DOLCE, and SUO can also be criticized for
> many reasons, and if there are fewer criticisms, part of the reason
> may be that they aren't as well known and haven't been as widely
> and thoroughly tested. I suspect that excluding Cyc from the
> process would be a recipe for producing another half vast product
> that would create more problems than solutions.
>
> The word 'amalgam' makes me think of a dentist mixing mercury with
> powdered silver. Far more critical to the development of an ontology
> is a well thought-out methodology that is able to accommodate an
> open-ended range of categories. Ideally, it should be able, in
> principle, to classify *every* category that anyone has ever
> conceived -- including everything in BFO, DOLCE, SUO, *and* Cyc
> *and* anything that anyone might ever come up with in the future.
>
> If you have such a methodology and suitable software to support it,
> you can take all the categories of all the ontologies, dump them
> in the hopper, turn the crank, and see how they are related to
> one another in the universal scheme.
>
> From that approach, you can pick a useful subset with confidence
> that more categories can be added at any time without disrupting
> applications that use the subset.
>
> AA> The ontologies proposed are of restricted importance, and
> > hardly will make any useful standards, see the synopsis on
> > STANDARD ONTOLOGY: the Standard Model of Reality, Representation
> > and Reasoning....
>
> Since I believe that all serious contenders should be considered,
> I would recommend that your categories be added to the mix as
> well as Cyc's.
>
> RHM> I offer as a reasonable standard the tabula rasa ontology
>
> Starting with a blank slate is useful, but any concept that
> anyone has ever found useful must be accommodated. Leibniz
> had an even more fundamental starting point: the number 1,
> which represented the universal Entity.
>
> RHM> It has a small number of fundamental concepts which are
> > likely to be used in all applications.
>
> Those are included in the starting ontologies recommended above.
>
> RHM> By contrast, most other ontologies are similar to Sowa's
> > ontology... which "mixes" three different views of existents,
> > thereby "cluttering" the ontology with concepts which may not
> > be used in a particular application.
>
> When people buy a dictionary, they get thousands of words they
> don't know -- that's the point. For children and students who
> are learning a language, there are smaller learner's dictionaries.
> There are also specialized dictionaries for special applications,
> but it's important to ensure that all the special cases are
> compatible with the general framework.
>
> For beginners who don't want to see the clutter, I suggest that
> somebody should write an uncluttered primer with pointers to
> the "Big Book" for anybody who wants more.
>
> MB> The three sets of top level classes in the KR ontology are
> > fundamental, technology neutral and easy to explain to non
> > technical business subject matter experts. Any class of "Thing"
> > in a mid-level ontology of common things (for example contracts,
> > money, processes, events, parameters) can be identified as being
> > a child or descendant of one thing in each of those layers (e.g.
> > an independent, concrete, continuant thing). To this I would add
> > whole/part, set, time and so on.
> >
> > I have done this, and it works, and people like it, understand it
> > and use it to provide practical business review and validation
> > of semantics models.
>
> Thanks for the note of support. But I'd like to emphasize that
> I proposed the KR ontology as an *example* of how an ontology can
> be derived by a systematic methodology:
>
> 1. Start with fundamental distinctions, not categories.
>
> 2. Each distinction generates a pair (for a binary distinction)
> or a triplet (for a ternary distinction) of basic features.
>
> 3. Leibniz's methodology derives all possible combinations of
> those features, which include many unnamed categories. Other
> methodologies (such as FCA) create lattices that minimize
> the number of unnamed categories.
>
> 4. If more categories and distinctions are added to the list,
> a new lattice can be derived that subsumes the earlier
> lattice as a proper subset.
>
> As an example of such a methodology with open-source software,
> I suggest Formal Concept Analysis (FCA). See the FCA home page:
>
> http://www.upriss.org.uk/fca/fca.html
>
> John
>
>
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> (06)
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