Looking for input regarding Basic Formal Ontology (BFO)
Michael DeBellis
David Whitten
Does anyone have any experience or opinions on BFO? Here is their web site: http://ifomis.uni-saarland.de/bfo/ Someone has approached me wanting to use some of my work but they want it to be built on BFO. BFO seems to be one of those Upper Models that provides a foundation for everything else. My concern is that from an initial look it seems to have its own definitions of things like Is-A, subsumption, relations, etc. that aren't the same as OWL. But this is only after a very brief look so I could be wrong. I'm curious if anyone has opinions, either positive or negative regarding it.
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Jack Hodges
Michael DeBellis
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Obrst, Leo J.
The main problem is that when you convert FOL theories to OWL you lose expressivity, and so you either annotate the axioms you want to apply or you extend the OWL into something like logic programming (Prolog, etc.), perhaps using Rule Interchange Format (RIF) as a “linking” syntax, or even Common Logic (or, previously, KIF). The main issue is that you can’t do consistently tractable automated reasoning (by definition) unless you use less expressive knowledge representation. There are tricks, and of course there are risks you assume when you use more expressive reasoners, balancing their value against their semi-decidability/general intractability. Probably most everyone knows this, so I apologize for stating the obvious.
There is quite a reduction from the original BFO, DOLCE, etc., FOL theories to OWL, so you will have a fair information loss. This means that except loosely, it is somewhat difficult to differentiate in general crucial distinctions among those except by interpreting the comments, and so some of the distinctions are not so distinguishable.
That is why we tend to create an agnostic circumscription around our mid-level and domain ontologies, establishing a kind of “scaffolding” of top-level notions within these that the mid-level/domain stuff can be put under. It means that we don’t “commit” early to an upper/foundational ontology, in order to do quicker real work at the mid/domain level (given that we have good knowledge of those upper distinctions, in advance). And it potentially enables mapping your ontologies to various upper/foundational ontologies, based e.g., at least partially on policy decisions regarding which architectures/communities, etc., your organization/community wants to commit to.
By the way, being “agnostic” does not come without peril/issues, because there may be additional work to create integration/bridge ontologies between your specific mid/domain ontology and specific upper/foundational ontologies, some more than others.
I am a firm believer in using upper/foundational ontologies, given that they sort out in principled ways the distinctions you will need to make (but that you personally are not necessarily proficient enough in the relevant issues to make; believe me, there are many personal anecdotes about these I can provide, but won’t), but on a given specific ontology project at lower levels, you can spend too much time worrying about linkages to those, rather than focusing on your specific lower-level ontology needs. But you need to gauge your own ontology strengths. E.g., some domain ontology projects focus most of their time on temporal and spatial issues, and then get those wrong, where they could have been tremendously helped by upper/foundational ontologies.
My two cents, a pragmatic approach that works for some, not all.
By the way, BFO is intentionally a succinct upper/foundational ontology.
Thanks,
Leo
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Michael DeBellis
Barry Smith
I was going off of what I read in the BFO Specification and User's guide which can be found on one of the links here: https://github.com/bfo-ontology/BFO/wikiSo for example in section 2.5 they talk about how is_a is "overloaded" and then give four examples that are perfectly clear (to me anyway) in OWL. The examples are:
a) a human being is a mammalb) a professor is a humanc) John is a human beingd) a restaurant in Palo Alto is a restaurant
To me these aren't perplexing at all. A and B are subclass relations and c and d are examples of set membership. BFO distinguishes between each of these. So in BFO a and b are two different kinds of relations and also c and d. I didn't exactly understand the distinction they are making. I think it has to do with their notion of universals which I think is based on work in philosophy which I think is of no value. Not philosophy in general I mean the philosophical notion of universals. I think its based on a very out-dated view of science and language. Chomsky talks about how Quine and others have an incorrect view of universals. I agree with Chomsky and think his criticism applies to the notion of universals used in BFO.
Or another example, section 2.7 BFO supports the "monohiearchy principle" which is single inheritance. I can see why one would want single inheritance for an OO programming language, I'm in the single inheritance camp myself when it comes to OOP but when it comes to modeling I think multiple inheritance is very useful and there is no problem understanding the semantics. Again its just set theory.
Also, BFO seems to have their own way of defining relations, transitivity, inverses, etc. that is different than the standard OWL functionality.
In all these cases I think the way OWL does it is more elegant and makes more sense to me but the real issue is that it seems to me that BFO isn't what I think of as a true OWL upper model, its not taking the normal semantics of OWL and just defining re-usable higher order classes that can be leveraged by all sorts of domains but rather it has its own modeling language that perhaps could be built on OWL but could not leverage the standard OWL capabilities. For example, based on what I've read I don't think it would be possible to use Protege to develop BFO ontologies, one would need to use modeling tools tuned to the BFO model.
There is a supposed OWL version of BFO 2.0 (one of the links under Implementation on the Wiki link above) but I downloaded it and brought it up in Protege. Its nothing but a bunch of class definitions. Literally nothing else, no object or data properties or rules so of course none of the classes are defined classes they are all just subclass relations.
But my look has also been very cursory so if you or others disagree I might be misunderstanding it.
Michael
On Wednesday, April 12, 2017 at 2:20:22 PM UTC-7, David Whitten wrote:
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Patrick Cassidy
Jack –
If you want more detail in an OWL upper ontology, perhaps you should check out the COSMO ontology – it has 9000 types (classes) and is intended to include all of the primitive concepts needed to logically specify the meaning of anything else. For many purposes, it would need to be converted to FOL but in OWL it has the virtue of being verifiable for logical consistency.
See: http://www.micra.com/COSMO/COSMO.owl
The parent folder has additional discussion of the ontology.
I will be happy to discuss any issues that are unclear in that ontology. If you find missing primitives (some basic concepts you need to logically specify the meanings of your local concepts) that are not included in that ontology please let me know – I am eager to supplement it to improve its ability to serve as a universal logical interlingua.
Pat
Patrick Cassidy
MICRA Inc.
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Jack Hodges
Sent: Wednesday, April 12, 2017 6:08 PM
To: ontolog-forum
Subject: Re: [ontolog-forum] Looking for input regarding Basic Formal Ontology (BFO)
Having worked quite a bit on object, behavior, and function causal models, when I was pointed to BFO as an object ontology I was quite excited. I have a copy of BFO 2 in RDF and I was very disappointed to find that it is very UNstructured in terms of class restrictions, inheritance, property domain and range specifications. But I was particularly disappointed to see embedded logic in CLIF strings. The example above is a good illustration. This is not what I think of when I think of OWL ontologies. The website says that it is an upper level ontology, so it wouldn't be expected to have much structure, but I would expect more structure than, say, DUL.
Jack Hodges
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Michael DeBellis
Barry Smith
thanks for the feedback so far its been very
thanks for the feedback so far its been very
Thanks to everyone for the feedback so far, very useful. I have a follow up question: what tool(s) are currently recommended for developing ontologies on top of BFO? Is Protege for example supposed to be considered a valid tool?
As I said in an earlier comment, the OWL BFO model that I saw was very basic, nothing but class definitions, no properties and hence no defined classes or rules.
I don't see how one could really get much value from starting by that model with Protege. Specifically, if I wanted to use BFO in Protege and I wanted to define a relation how would I do it? Normally I would just define an object property but my interpretation of BFO (as always please correct me if I'm wrong) is that the BFO relations are so different that I couldn't do that.
So if not that then how? And the same thing for subclassing or creating instances. BFO seems to have different variants of both (under the title of is-a overloading) where as OWL just has one concept for each so again can't see how this would work with OWL.
And if I can't use Protege to build an ontology on top of BFO then what tool do I use? I saw one release in a tool which I think was called Isabella and to my recollection is a theorem prover. Is that the way to do it or if not how?
Michael
On Wednesday, April 12, 2017 at 1:48:06 PM UTC-7, Michael DeBellis wrote:
Does anyone have any experience or opinions on BFO? Here is their web site: http://ifomis.uni-saarland.de/bfo/ Someone has approached me wanting to use some of my work but they want it to be built on BFO. BFO seems to be one of those Upper Models that provides a foundation for everything else. My concern is that from an initial look it seems to have its own definitions of things like Is-A, subsumption, relations, etc. that aren't the same as OWL. But this is only after a very brief look so I could be wrong. I'm curious if anyone has opinions, either positive or negative regarding it.
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John F Sowa
Whenever I look at BFO examples, they remind me of the debates
we have been having for nearly a quarter of a century.
An excerpt from
https://raw.githubusercontent.com/oborel/obo-relations/master/core.owl :
> A continuant cannot have an occurrent as part: use 'participates in'.
> An occurrent cannot have a continuant as part: use 'has participant'.
> An immaterial entity cannot have a material entity as part:
> use 'location of'.
> An independent continuant cannot have a specifically dependent
> continuant as part: use 'bearer of'.
> A specifically dependent continuant cannot have an independent
> continuant as part: use 'inheres in'.
> ...
> Parthood requires the part and the whole to have compatible classes:
> only an occurrent can have an occurrent as part; only a process can
> have a process as part; only a continuant can have a continuant as part;
This is a very rigid set of axioms. They look precise until you ask
what kinds of things might be continuants or occurrents.
A glacier, for example, seems quite rigid during the winter, but
during the summer it has waterfalls as part. Even in the winter,
it creeps along slowly, but surely. The major difference between
a glacier and a lava flow is time scale and point of view -- i.e.,
the *intentions* of the people who are describing the things.
From the same document:
> the surface of my skin is a 2D boundary of my body...
> a relation between a 2D immaterial entity (the boundary) and
> a material entity, in which the boundary delimits the material entity
In physics, there is no such thing as a 2D boundary. At the most
fundamental level, every physical entity is a process. It has a
continuous wave function that trails off to infinity.
Continuants are processes whose rate of change is slow compared
to whatever time scale is chosen for the description.
For applications, the choice of description depends strongly on
the kind of application. Consider a surgeon who is cutting the
skin, a dermatologist who is examining it, a makeup artist who
is painting it, a tattoo artist who is creating a design...
None of those people think "2D".
For living things, life itself is a process. And every organism
has a goal (intention) of maintaining and enhancing its life.
Intentions are not just anthropomorphic, they are biomorphic.
For that matter, human beings are anthropomorphic. Every aspect
of *applied* ontology is determined by some humans who design
an application for some purpose. Form follows function.
Summary: Intentionality is the starting point for any application.
Any foundation for applied ontology must recognize and support
intentionality in all its aspects.
John
Edward Barkmeyer
> Whenever I look at BFO examples, they remind me of the debates we have been having for nearly a quarter of a century.
There are doubtless philosophical and practical arguments that persuade you to choose Cyc or DOLCE or SUMO or BFO for a given purpose. But this is largely a matter of "taste". For a given application, the only question for us engineers is: does BFO help me get the "right" results?
-Ed
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Barry Smith
during the summer it has waterfalls as part. Even in the winter,
a glacier and a lava flow is time scale and point of view -- i.e.,
the *intentions* of the people who are describing the things.
From the same document:
> the surface of my skin is a 2D boundary of my body...
> a relation between a 2D immaterial entity (the boundary) and
> a material entity, in which the boundary delimits the material entity
In physics, there is no such thing as a 2D boundary. At the most
fundamental level, every physical entity is a process. It has a
continuous wave function that trails off to infinity.
Continuants are processes whose rate of change is slow compared
to whatever time scale is chosen for the description.
For applications, the choice of description depends strongly on
the kind of application. Consider a surgeon who is cutting the
skin, a dermatologist who is examining it, a makeup artist who
is painting it, a tattoo artist who is creating a design...
None of those people think "2D".
For living things, life itself is a process.
has a goal (intention) of maintaining and enhancing its life.
Intentions are not just anthropomorphic, they are biomorphic.
For that matter, human beings are anthropomorphic. Every aspect
of *applied* ontology is determined by some humans who design
an application for some purpose. Form follows function.
Summary: Intentionality is the starting point for any application.
Any foundation for applied ontology must recognize and support
intentionality in all its aspects.
Chris Mungall
On 14 Apr 2017, at 8:03, John F Sowa wrote:
> Barry,
>
> Whenever I look at BFO examples, they remind me of the debates
> we have been having for nearly a quarter of a century.
moved on from these debates, but this forum seems stuck.
Disclosure, I'm one of the developers of the RO.
>> A continuant cannot have an occurrent as part: use 'participates in'.
>> An occurrent cannot have a continuant as part: use 'has participant'.
>> An immaterial entity cannot have a material entity as part:
>> use 'location of'.
>> An independent continuant cannot have a specifically dependent
>> continuant as part: use 'bearer of'.
>> A specifically dependent continuant cannot have an independent
>> continuant as part: use 'inheres in'.
>> ...
>> Parthood requires the part and the whole to have compatible classes:
>> only an occurrent can have an occurrent as part; only a process can
>> have a process as part; only a continuant can have a continuant as
>> part;
>
> This is a very rigid set of axioms. They look precise until you ask
> what kinds of things might be continuants or occurrents.
model-theoretic precision of the underlying OWL constructs.
> A glacier, for example, seems quite rigid during the winter, but
> during the summer it has waterfalls as part. Even in the winter,
> it creeps along slowly, but surely. The major difference between
> a glacier and a lava flow is time scale and point of view -- i.e.,
> the *intentions* of the people who are describing the things.
we model glaciers as continuants:
http://purl.obolibrary.org/obo/ENVO_00000133
The speed of their movement is irrelevant. Rocks and rivers are also
modeled as continuants in this ontology.
There is no laval flow process in this ontology, but if it were it might
be a sibling of this:
http://purl.obolibrary.org/obo/ENVO_01000697
There have been various philosophical discussions on this list about the
pros and cons of distinguishing continuants vs occurrents. In our
experience the distinction is pragmatic and no domain specialist or
ontology developer typically has a problem with the distinction.
> From the same document:
>> the surface of my skin is a 2D boundary of my body...
>> a relation between a 2D immaterial entity (the boundary) and
>> a material entity, in which the boundary delimits the material entity
>
> In physics, there is no such thing as a 2D boundary. At the most
> fundamental level, every physical entity is a process. It has a
> continuous wave function that trails off to infinity.
treating 2D boundaries as real.
I'm not so concerned, I think of these as useful abstractions,
especially for anatomy. It's also very useful to filter out all
abstractions such as boundaries for purposes such as using an anatomy
ontology to describe sites of gene expression.
>
> Continuants are processes whose rate of change is slow compared
> to whatever time scale is chosen for the description.
>
> For applications, the choice of description depends strongly on
> the kind of application. Consider a surgeon who is cutting the
> skin, a dermatologist who is examining it, a makeup artist who
> is painting it, a tattoo artist who is creating a design...
> None of those people think "2D".
abstractions like points in our anatomy ontologies. But these are
excluded for other purposes, e.g. gene expression.
> For living things, life itself is a process. And every organism
> has a goal (intention) of maintaining and enhancing its life.
> Intentions are not just anthropomorphic, they are biomorphic.
> For that matter, human beings are anthropomorphic. Every aspect
> of *applied* ontology is determined by some humans who design
> an application for some purpose. Form follows function.
>
> Summary: Intentionality is the starting point for any application.
> Any foundation for applied ontology must recognize and support
> intentionality in all its aspects.
Some people like (or dislike) BFO based on their view of reality
But for most people developing domain ontologies, it provides a handy
convention for an absolute minimum level of interoperation across
multiple semi-independent efforts.
> John
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Adam Pease
number of years ago that I wish would gain a bit more traction. An
objective standard for the quality of an ontology can be what one can
conclude from it in automated theorem proving. We all may have various
intuitions about the right way to approach certain issues, but once one
actually has to formalize them in a particular logic and use a
particular theorem prover to reach a conclusion, a lot of these debates
disappear.
If one picks an expressive logic and powerful theorem prover (like
BFO has with Isabelle, or as SUMO has with E, for FOL and LEO-II for
HOL) then one is left with the concrete task of formalizing all these
intuitions and seeing if they work in practice. A limited logic or a
handful of axioms will allow few conclusions and lay bare one's assumptions.
all the best,
Adam
On 04/14/2017 08:28 AM, Barry Smith wrote:
> John
> These are indeed familiar questions. BFO's insistence upon the
> distinction between continuants and occurrents is best understood as a
> traffic law. If everyone follows it, there will be, to that degree, more
> well-behaved traffic.
>
> A glacier, for example, seems quite rigid during the winter, but
> during the summer it has waterfalls as part. Even in the winter,
> it creeps along slowly, but surely. The major difference between
> a glacier and a lava flow is time scale and point of view -- i.e.,
> the *intentions* of the people who are describing the things.
>
> We start out from the idea that molecules, cells, organisms are
> continuants. You, for instance. You gain and lose parts more or less
> slowly. You are still a continuant. Someone may look at all the parts of
> you at a very fine level of granularity and see a lot of motion. But you
> are still a continuant. (See the treatment of Eddington's two tables,
> e.g. here):
> the sum of processes in which these are involved is an occurrent. The
> forest fire is a continuant. Its passage through the forest is an occurrent.
>
> From the same document:
>> the surface of my skin is a 2D boundary of my body...
>> a relation between a 2D immaterial entity (the boundary) and
>> a material entity, in which the boundary delimits the material entity
>
> In physics, there is no such thing as a 2D boundary. At the most
> fundamental level, every physical entity is a process. It has a
> continuous wave function that trails off to infinity.
>
> Continuants are processes whose rate of change is slow compared
> to whatever time scale is chosen for the description.
>
> This is an interesting traffic law. But we have chosen a different one.
> Some ontology developers, for instance Mathew West, choose to follow
> your preferred traffic law. Some others
>
> For applications, the choice of description depends strongly on
> the kind of application. Consider a surgeon who is cutting the
> skin, a dermatologist who is examining it, a makeup artist who
> is painting it, a tattoo artist who is creating a design...
> None of those people think "2D".
>
> People who worry about anatomy see the need for a structural anatomy
> which forms the basis (and provides a useful framework of traffic laws)
> for all of these (and thereby adopt a BFO point of view)
> For living things, life itself is a process.
>
>
> And every organism
> has a goal (intention) of maintaining and enhancing its life.
> Intentions are not just anthropomorphic, they are biomorphic.
>
> Exactly
>
> For that matter, human beings are anthropomorphic. Every aspect
> of *applied* ontology is determined by some humans who design
> an application for some purpose. Form follows function.
>
> Exactly. Indeed tautologously.
>
> Summary: Intentionality is the starting point for any application.
> Any foundation for applied ontology must recognize and support
> intentionality in all its aspects.
>
> Perhaps the Mental Functioning Ontology
> Emotion Ontology <http://www.ontobee.org/ontology/MFOEM> will make you
> <mailto:ontolog-forum%2Bunsu...@googlegroups.com>.
>
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> content license, open publication license, open source or free software
> license. Unless otherwise specified, all Ontolog Forum content shall be
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Adam Pease
http://www.ontologyportal.org
http://www.adampease.org
Bruce Schuman
The specification on Basic Formal Ontology 2.0 (BFO) develops the very illuminating distinction between a “fiat boundary” and “bona fide boundary”.
https://github.com/BFO-ontology/BFO/raw/master/docs/bfo2-reference/BFO2-Reference.pdf
I saw this tension emerge when I read Applied Ontology – An Introduction a couple years ago
http://ontology.buffalo.edu/AppliedOntology.pdf
where I seemed to sense a kind of preference of among some of the authors for natural (bona fide) boundaries on the grounds that they are more “realistic”.
So it was interesting to see this mention of “fiat boundaries” in the BFO specification.
This is an important foundational concept, and it is treated in detail here:
http://ontology.buffalo.edu/smith/articles/fiat-boundaries.pdf
My own assumption is that our real objective (as cognitive scientists or computer scientists) is the representation of both fiat boundaries and natural (bona fide) boundaries in terms of abstract symbolism and an alphabet. In this symbolic and representational/abstract context, it can be argued that all definition and boundaries are “stipulative” – or asserted for some intentional reason (as per JS comment below). We represent (empirical) reality in terms of (abstract) symbolism and then as scientists attempt to reduce uncertainty and error (to zero) in the abstract representation.
This process amounts to a kind of convergence between fiat boundary (abstract symbolism) and bona fide boundary (empirical reality). And it looks to me like “fiat boundary” and “stipulative definition” are either very similar or identical.
So, in the search for universal method, it makes sense to generalize the process of symbolic representation as always involving stipulative or fiat boundaries and definitions. That’s the best we can do with language and measurement – and computer models.
JS:
>For that matter, human beings are anthropomorphic. Every aspect
>of *applied* ontology is determined by some humans who design
>an application for some purpose. Form follows function.
>Summary: Intentionality is the starting point for any application.
>Any foundation for applied ontology must recognize and support
>intentionality in all its aspects.
Yes, absolutely.
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Barry Smith
Sent: Friday, April 14, 2017 8:29 AM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Re: Looking for input regarding Basic Formal Ontology (BFO)
John
These are indeed familiar questions. BFO's insistence upon the distinction between continuants and occurrents is best understood as a traffic law. If everyone follows it, there will be, to that degree, more well-behaved traffic.
A glacier, for example, seems quite rigid during the winter, but
during the summer it has waterfalls as part. Even in the winter,
it creeps along slowly, but surely. The major difference between
a glacier and a lava flow is time scale and point of view -- i.e.,
the *intentions* of the people who are describing the things.
We start out from the idea that molecules, cells, organisms are continuants. You, for instance. You gain and lose parts more or less slowly. You are still a continuant. Someone may look at all the parts of you at a very fine level of granularity and see a lot of motion. But you are still a continuant. (See the treatment of Eddington's two tables, e.g. here): Your life is an occurrent. The glacier (and the waterfall) is a continuant; the sum of processes in which these are involved is an occurrent. The forest fire is a continuant. Its passage through the forest is an occurrent.
From the same document:
> the surface of my skin is a 2D boundary of my body...
> a relation between a 2D immaterial entity (the boundary) and
> a material entity, in which the boundary delimits the material entity
In physics, there is no such thing as a 2D boundary. At the most
fundamental level, every physical entity is a process. It has a
continuous wave function that trails off to infinity.
That is why BFO refers to them as fiat 2D (etc.) boundaries
Continuants are processes whose rate of change is slow compared
to whatever time scale is chosen for the description.
This is an interesting traffic law. But we have chosen a different one. Some ontology developers, for instance Mathew West, choose to follow your preferred traffic law. Some others choose the traffic law preferred by BFO.
For applications, the choice of description depends strongly on
the kind of application. Consider a surgeon who is cutting the
skin, a dermatologist who is examining it, a makeup artist who
is painting it, a tattoo artist who is creating a design...
None of those people think "2D".
People who worry about anatomy see the need for a structural anatomy which forms the basis (and provides a useful framework of traffic laws) for all of these (and thereby adopt a BFO point of view).
For living things, life itself is a process.
Exactly
And every organism
has a goal (intention) of maintaining and enhancing its life.
Intentions are not just anthropomorphic, they are biomorphic.
Exactly
For that matter, human beings are anthropomorphic. Every aspect
of *applied* ontology is determined by some humans who design
an application for some purpose. Form follows function.
Exactly. Indeed tautologously.
Summary: Intentionality is the starting point for any application.
Any foundation for applied ontology must recognize and support
intentionality in all its aspects.
Perhaps the Mental Functioning Ontology can help with that and perhaps the Emotion Ontology will make you happy.
BS.
On Fri, Apr 14, 2017 at 11:03 AM, John F Sowa <so...@bestweb.net> wrote:
Barry,
Whenever I look at BFO examples, they remind me of the debates
we have been having for nearly a quarter of a century.
An excerpt from
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Chris Mungall
On 14 Apr 2017, at 8:23, Edward Barkmeyer wrote:
> John,
>
>> Whenever I look at BFO examples, they remind me of the debates we
>> have been having for nearly a quarter of a century.
>
> I would hope so. And another few hundred years, as your own writing
> attests. That is what ontology of the philosophical kind is famous
> for, and what "upper ontology" necessarily comes to grips with. If
> you decide to use one, in whole or in part, you have to accept the
> philosophical choices they made, at least in what you adopt, or toss
> it in the "maybe never" box and look at another one.
>
> There are doubtless philosophical and practical arguments that
> persuade you to choose Cyc or DOLCE or SUMO or BFO for a given
> purpose. But this is largely a matter of "taste". For a given
> application, the only question for us engineers is: does BFO help me
> get the "right" results?
And one of the advantages of BFO is that doesn't really get in the way
engineering-wise (generally). The ontological commitments are generally
at a high level of abstraction, and don't get in the way of your domain.
This is maybe frustrating if you're looking for more explicit guidance
on how to model particular things in OWL, but YMMV.
I have seen people go to town and model every aspect of an entity using
half of the categories in BFO, leading to inflation in the number of
ontology classes, and results that can be unintuitive for users. But
this can easily be avoided.
Chris Mungall
On 13 Apr 2017, at 20:18, Michael DeBellis wrote:
> thanks for the feedback so far its been very
> thanks for the feedback so far its been very
> follow up
> question: what tool(s) are currently recommended for developing
> ontologies
> on top of BFO? Is Protege for example supposed to be considered a
> valid
> tool?
supporting tools that help with various aspects such as building
ontologies up from shared design patterns.
Some of the OBO tutorial may be useful
https://github.com/jamesaoverton/obo-tutorial-icbo-2017/
We'll be giving this tutorial at ICBO in Newcastle UK later this year.
It's geared towards biological ontologies but much should be
transferable.
> As I said in an earlier comment, the OWL BFO model that I saw was
> very basic, nothing but class definitions, no properties and hence no
> defined classes or rules. I don't see how one could really get much
> value
> from starting by that model with Protege. Specifically, if I wanted to
> use
> BFO in Protege and I wanted to define a relation how would I do it?
consistent with BFO
http://purl.obolibrary.org/obo/ro/core.owl
> Normally I would just define an object property but my interpretation
> of
> BFO (as always please correct me if I'm wrong) is that the BFO
> relations
> are so different that I couldn't do that.
least in the life sciences ontology community, everything is done in
OWL. It may be different for other communities that use BFO.
> So if not that then how? And the
> same thing for subclassing or creating instances. BFO seems to have
> different variants of both (under the title of is-a overloading) where
> as
> OWL just has one concept for each so again can't see how this would
> work
> with OWL.
that talks about single inheritance.
> And if I can't use Protege to build an ontology on top of BFO then
> what
> tool do I use? I saw one release in a tool which I think was called
> Isabella and to my recollection is a theorem prover. Is that the way
> to do
> it or if not how?
you use here should be dictated by engineering considerations (what
inferences you need, etc), not what upper ontology you use.
> Michael
> On Wednesday, April 12, 2017 at 1:48:06 PM UTC-7, Michael DeBellis
> wrote:
>>
>> Does anyone have any experience or opinions on BFO? Here is their web
>> site: http://ifomis.uni-saarland.de/bfo/ Someone has approached me
>> wanting to use some of my work but they want it to be built on BFO.
>> BFO
>> seems to be one of those Upper Models that provides a foundation for
>> everything else. My concern is that from an initial look it seems to
>> have
>> its own definitions of things like Is-A, subsumption, relations, etc.
>> that
>> aren't the same as OWL. But this is only after a very brief look so I
>> could
>> be wrong. I'm curious if anyone has opinions, either positive or
>> negative
>> regarding it.
>>
>
Michael DeBellis
Michael DeBellis
On Wednesday, April 12, 2017 at 1:48:06 PM UTC-7, Michael DeBellis wrote:
Matthew West
Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
1. Do you think that physical objects pass through time, or do you think they are extended in time (as well as space)?
2. Do you think classes/types (e.g. bicycle) always have the same members, or do you think membership can change over time?
3. Do you think that an activity can also be a physical object, or do you think that activities and physical objects are quite separate things?
What you can’t do is say “both” because that will lead immediately to a contradiction (nor can say “neither”). The choices you make (and these are just a sample) are your ontological commitments, and a Top Level Ontology is principally a particular set of these ontological commitments. BFO exemplifies such a set of ontological commitments, a different set is exemplified by ISO 15926-2 (or my book “Developing High Quality Data Models”).
The value then of the TLO is that you can check your domain ontology against it to make sure it conforms to your chosen ontological commitments. This is where the traffic lights come in.
It turns out that if you just toss a coin to make your choices on these questions, most of the combinations are not coherent, but there are two combinations (with variations) that are reasonably coherent (though proponents of each will argue that the other is not really). These I will characterise as 3D and 4D:
3D (e.g. BFO)
1. Physical objects pass through time and are wholly present at each point in time.
2. Classes/types can change members over time (For the type car, the number of cars is different today and yesterday).
3. A physical object cannot also be an activity.
4D (e.g. ISO 15926)
1. Physical objects are extended in time as well as space.
2. Classes are defined by their membership (they are sets). So, the type car is the set of cars over all time, cars yesterday is a subset of this.
3. Physical objects and activities can overlap, so a person is their life, not separate from it.
Regards
Matthew West
Information Junction
Mobile: +44 750 3385279
Skype: dr.matthew.west
matthe...@informationjunction.co.uk
http://www.informationjunction.co.uk/
https://www.matthew-west.org.uk/
This email originates from Information Junction Ltd. Registered in England and Wales No. 6632177.
Registered office: 8 Ennismore Close, Letchworth Garden City, Hertfordshire, SG6 2SU.
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Michael DeBellis
Sent: 25 April 2017 03:48
To: ontolog-forum <ontolo...@googlegroups.com>
rrov...@buffalo.edu
Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
Again, the fact is that the generality is so high that there may not be an implicit top-level in the minds of the developers. If there is one it may be of a vague, undetermined and underspecified nature. Afterall, non-philosophers, non-specialists in this area, do not usually (let alone instinctively) consider persistence and other formal ontological aspects. It's an exercise in part in psychology vis-a-vis concepts. Studies may suggest fundamental concepts, e.g. living vs. non-living. But these do not necessarily change over time to become a full-fledged implicit top-level conceptualization in the minds of developers underlying their explicitly specified domain ontology.
This is not to say that no one has implicit top-level ideas in mind, nor is it to say that they might not want to use some particular top-level conceptualization.
But it is quite another to suggest a domain developer definitely has an implicit TLO or must have one, or must select from a set of pre-existing distinctions (e.g. 1-3 below). Pre-existing distinctions may not be sufficient, may not be what they think of.
1. Do you think that physical objects pass through time, or do you think they are extended in time (as well as space)?
2. Do you think classes/types (e.g. bicycle) always have the same members, or do you think membership can change over time?
3. Do you think that an activity can also be a physical object, or do you think that activities and physical objects are quite separate things?
What you can’t do is say “both” because that will lead immediately to a contradiction (nor can say “neither”).
But in any case, it would be helpful for this forum to show how any contradiction would arise...
The choices you make (and these are just a sample) are your ontological commitments, and a Top Level Ontology is principally a particular set of these ontological commitments. BFO exemplifies such a set of ontological commitments, a different set is exemplified by ISO 15926-2 (or my book “Developing High Quality Data Models”).
The value then of the TLO is that you can check your domain ontology against it to make sure it conforms to your chosen ontological commitments. This is where the traffic lights come in.
It turns out that if you just toss a coin to make your choices on these questions, most of the combinations are not coherent, but there are two combinations (with variations) that are reasonably coherent (though proponents of each will argue that the other is not really). These I will characterise as 3D and 4D:
3D (e.g. BFO)
1. Physical objects pass through time and are wholly present at each point in time.
2. Classes/types can change members over time (For the type car, the number of cars is different today and yesterday).
4D (e.g. ISO 15926)
1. Physical objects are extended in time as well as space.
2. Classes are defined by their membership (they are sets). So, the type car is the set of cars over all time, cars yesterday is a subset of this.
3. Physical objects and activities can overlap, so a person is their life, not separate from it.
Regards
Matthew West
Information Junction
Mobile: +44 750 3385279
Skype: dr.matthew.west
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Chris Partridge
Input in-line below...On Tue, Apr 25, 2017 at 12:02 PM, Matthew West <dr.matt...@gmail.com> wrote:Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
That's a interesting way to put it. But I would not insist that there is a TLO inside or implicit, though. Why? Because the domain developers may in fact either not have conceptualized a more abstract level or any implicit or subconscious concepts are so flexible that they underdetermine any particular would-be top-level. The investigation into any implicit top-level is an exploration into great abstractness, and can lead into confusion. It can lead to domain ontology developers feeling forced to select or identify what any supposed implicit top-level their domain ontology has. Which they don't. They should also not feel they have to adopt a particular pre-existing conceptualization, category or distinction (e.g. the continuant vs. occurrent).
Styrman, Avril E R
Dear Michael, some comments.
Chris Partridge
Dear Michael, some comments.
From: ontolo...@googlegroups.com <ontolog-forum@googlegroups.com> on behalf of Michael DeBellis <mdebe...@gmail.com>
--
rrov...@buffalo.edu
inline a few comments ...and one general comment. Your identification of the various ontological options is good, and it seems to me (from an engineering point of view) that one should explore whether and how they work. I hope that is what you are recommending.On 25 April 2017 at 13:03, <rrov...@buffalo.edu> wrote:Input in-line below...On Tue, Apr 25, 2017 at 12:02 PM, Matthew West <dr.matt...@gmail.com> wrote:Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
That's a interesting way to put it. But I would not insist that there is a TLO inside or implicit, though. Why? Because the domain developers may in fact either not have conceptualized a more abstract level or any implicit or subconscious concepts are so flexible that they underdetermine any particular would-be top-level. The investigation into any implicit top-level is an exploration into great abstractness, and can lead into confusion. It can lead to domain ontology developers feeling forced to select or identify what any supposed implicit top-level their domain ontology has. Which they don't. They should also not feel they have to adopt a particular pre-existing conceptualization, category or distinction (e.g. the continuant vs. occurrent).CP> I am assuming that when you talk about domain ontology developers you mean domain experts rather than ontology experts - if I have misinterpreted, I apologise.CP> In my experience, there is a fundamental choice here for projects. Domain developers/ experts or ontologists first. And it is not that one is inherently right (for the kind of business system development I am interested in), it is just (for me) whether one ends up with a better product at a reasonable cost.
All the more better if each has knowledge and skills of the other (I think courses/training should be compulsory to each).
CP> In our BORO work, we take the ontologists first approach as we find it gives good results - in our experience most domain experts are not able to articulate fully what they know (for the more technically minded see Ryle on anti-intellectualism - also some of my papers) - we find data-driven approaches supplemented by experts a better route - one not available for all domains, as they may not have the right kind of structured data resources.
Would you please clarify 'data-driven approaches'?
CP> I agree that typically asking domain experts to identify the implicit top level leads to confusion, so we don't ask them (as an aside, this is common practice for business/conceptual modelling practitioners, even for simple non-ontological business models).
I did not say/mean not to ask them because it might lead to confusion. No, that would be wrong because ontologists need domain experts, and domain knowledge, to create accurate ontologies. Domain experts serve the essential task of (a) providing knowledge, (b) verifying ontological characterizations and ontology content, and (c) quality control...at least ideally!
It's possible that domain experts attempt to identify potential (but not necessarily actual) implicit top-level conceptualizations causes confusion, but not necessarily. What i meant was that because foundational ontological inquiry is so abstract with various concepts either concepts of art (jargon) or vague, the very inquiry itself can lead to confusion, particularly for people not versed in the respective concepts, in the formal analysis, and philosophical ontology. It's like formal logic: people need to be trained in it...FOL, for instance, does not come naturally. Likewise, I suspect, for formalizing top-level aspects. Hence, its easy to get into confusion. The concepts are so vague that a non-ontologist can easily (and rightly in many cases!) ask: "Why are you using that top-level category?", "Why do you define 'object', 'process', '...' that way and not another?", "Why do you say that continuants and occurrents are mutually exclusive?"
CP> However, I get the feeling you are suggesting that because the domain experts cannot be easily asked to make a choice, that this somehow means that this choice should not be made in the project. If you are suggesting this, I do not see the argument.
Chris Partridge
inline below again...On Tue, Apr 25, 2017 at 2:29 PM, Chris Partridge <partri...@gmail.com> wrote:inline a few comments ...and one general comment. Your identification of the various ontological options is good, and it seems to me (from an engineering point of view) that one should explore whether and how they work. I hope that is what you are recommending.On 25 April 2017 at 13:03, <rrov...@buffalo.edu> wrote:Input in-line below...On Tue, Apr 25, 2017 at 12:02 PM, Matthew West <dr.matt...@gmail.com> wrote:Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
That's a interesting way to put it. But I would not insist that there is a TLO inside or implicit, though. Why? Because the domain developers may in fact either not have conceptualized a more abstract level or any implicit or subconscious concepts are so flexible that they underdetermine any particular would-be top-level. The investigation into any implicit top-level is an exploration into great abstractness, and can lead into confusion. It can lead to domain ontology developers feeling forced to select or identify what any supposed implicit top-level their domain ontology has. Which they don't. They should also not feel they have to adopt a particular pre-existing conceptualization, category or distinction (e.g. the continuant vs. occurrent).CP> I am assuming that when you talk about domain ontology developers you mean domain experts rather than ontology experts - if I have misinterpreted, I apologise.CP> In my experience, there is a fundamental choice here for projects. Domain developers/ experts or ontologists first. And it is not that one is inherently right (for the kind of business system development I am interested in), it is just (for me) whether one ends up with a better product at a reasonable cost.By 'domain ontology developers' I mean either domain experts or ontology developers, but not necessarily ontology experts. The onto developers may be domain experts and may not.I believe having both domain experts (or non-ontologist ontology developers) and ontologists working together from the beginning is the best strategy.
All the more better if each has knowledge and skills of the other (I think courses/training should be compulsory to each).
CP> In our BORO work, we take the ontologists first approach as we find it gives good results - in our experience most domain experts are not able to articulate fully what they know (for the more technically minded see Ryle on anti-intellectualism - also some of my papers) - we find data-driven approaches supplemented by experts a better route - one not available for all domains, as they may not have the right kind of structured data resources.
Would you please clarify 'data-driven approaches'?
CP> I agree that typically asking domain experts to identify the implicit top level leads to confusion, so we don't ask them (as an aside, this is common practice for business/conceptual modelling practitioners, even for simple non-ontological business models).
I did not say/mean not to ask them because it might lead to confusion. No, that would be wrong because ontologists need domain experts, and domain knowledge, to create accurate ontologies. Domain experts serve the essential task of (a) providing knowledge, (b) verifying ontological characterizations and ontology content, and (c) quality control...at least ideally!
It's possible that domain experts attempt to identify potential (but not necessarily actual) implicit top-level conceptualizations causes confusion, but not necessarily. What i meant was that because foundational ontological inquiry is so abstract with various concepts either concepts of art (jargon) or vague, the very inquiry itself can lead to confusion, particularly for people not versed in the respective concepts, in the formal analysis, and philosophical ontology. It's like formal logic: people need to be trained in it...FOL, for instance, does not come naturally. Likewise, I suspect, for formalizing top-level aspects. Hence, its easy to get into confusion. The concepts are so vague that a non-ontologist can easily (and rightly in many cases!) ask: "Why are you using that top-level category?", "Why do you define 'object', 'process', '...' that way and not another?", "Why do you say that continuants and occurrents are mutually exclusive?"
CP> However, I get the feeling you are suggesting that because the domain experts cannot be easily asked to make a choice, that this somehow means that this choice should not be made in the project. If you are suggesting this, I do not see the argument.No, I do not suggest that. I meant that it's not correct that necessarily there is an implicit top-level conceptualization in a domain ontology or in the mind of domain experts. And I meant that ontologists should not try to pull some implicit top-level conceptualization from the minds of the domain experts if there isn't one, nor should they try to coax, convince or impose their own preferred top-level conceptualziation on domain experts. For example, the continuant-occurrent distinction (of a certain interpretation/sense of each category) is something that is often espoused time and again, asserted as being the way the top-level should be, but with little justification or explanation of historical origins. The oft-held mutual exclusivity of the categories is something typically not demonstrated when these dicussions take place (but they should because that has been contested in the literature). Some have questioned the interpretaion and sense of the categories, e.g., the wholly present aspect and other properties of each. The exchange between domain experts and ontologists is of course worth making, but the former may simply not have an implicit top-level in mind, may not agree with the top-level distinctions the ontologist introduces, etc. Also, the danger is that given the specialist knowledge in ontology development, and given domain expert lack of interest in such abstract levels, domain experts may simply accept whatever the ontologist says. This is not correct because they would be blindly accepting the onto commitments, metaphysical assumptions, methodologies, etc. And the consequences of this are that domain expert concepts and objects might be mischaracterized, falsely defined or pidgeonholed into this or that philosophical or methodological theory.
Styrman, Avril E R
Chris,
the range is wide, but we can identify the goal and work towards it. The
unity of science is not the same thing as a
unifying underlying ontology, but the unity of science cannot be achieved without a
unifying ontology in the center.
Avril
Sent: Wednesday, April 26, 2017 12:22:51 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Re: Looking for input regarding Basic Formal Ontology (BFO)
rrov...@buffalo.edu
inline again ...BTW there are different kinds of ontology projects, and we may just be talking about different kinds.On 26 April 2017 at 11:43, <rrov...@buffalo.edu> wrote:inline below again...On Tue, Apr 25, 2017 at 2:29 PM, Chris Partridge <partri...@gmail.com> wrote:inline a few comments ...and one general comment. Your identification of the various ontological options is good, and it seems to me (from an engineering point of view) that one should explore whether and how they work. I hope that is what you are recommending.On 25 April 2017 at 13:03, <rrov...@buffalo.edu> wrote:Input in-line below...On Tue, Apr 25, 2017 at 12:02 PM, Matthew West <dr.matt...@gmail.com> wrote:Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
That's a interesting way to put it. But I would not insist that there is a TLO inside or implicit, though. Why? Because the domain developers may in fact either not have conceptualized a more abstract level or any implicit or subconscious concepts are so flexible that they underdetermine any particular would-be top-level. The investigation into any implicit top-level is an exploration into great abstractness, and can lead into confusion. It can lead to domain ontology developers feeling forced to select or identify what any supposed implicit top-level their domain ontology has. Which they don't. They should also not feel they have to adopt a particular pre-existing conceptualization, category or distinction (e.g. the continuant vs. occurrent).CP> I am assuming that when you talk about domain ontology developers you mean domain experts rather than ontology experts - if I have misinterpreted, I apologise.CP> In my experience, there is a fundamental choice here for projects. Domain developers/ experts or ontologists first. And it is not that one is inherently right (for the kind of business system development I am interested in), it is just (for me) whether one ends up with a better product at a reasonable cost.By 'domain ontology developers' I mean either domain experts or ontology developers, but not necessarily ontology experts. The onto developers may be domain experts and may not.I believe having both domain experts (or non-ontologist ontology developers) and ontologists working together from the beginning is the best strategy.
All the more better if each has knowledge and skills of the other (I think courses/training should be compulsory to each).
CP> In our BORO work, we take the ontologists first approach as we find it gives good results - in our experience most domain experts are not able to articulate fully what they know (for the more technically minded see Ryle on anti-intellectualism - also some of my papers) - we find data-driven approaches supplemented by experts a better route - one not available for all domains, as they may not have the right kind of structured data resources.
Would you please clarify 'data-driven approaches'?CP> A typical example is a legacy modernisation project, where there is an existing operational system (SAP or Oracale Financials or ...). The task is to migrate the data to a new system or to a data warehouse or ...CP> My argument has been for a while (see e.g. my 1996 book) that people are not really up to the task of specifying things to the level of detail needed by computers, so existing operational data has at least the merit of being proved to work. And I'm suspicious of experts' expertise. Searle (somewhere, maybe social construction) has a few paragraphs where he makes the point that experts usually don't know in terms of being able to articulate, and sometimes evaluate, their knowledge - and as I said earlier there is the whole Ryle anti-intellectualism debate that has heated up recently. Not saying that experts aren't needed, just that they need to have the right kind of role.
Do you have a link to that debate/paper and is your book available in pdf?
CP> I agree that typically asking domain experts to identify the implicit top level leads to confusion, so we don't ask them (as an aside, this is common practice for business/conceptual modelling practitioners, even for simple non-ontological business models).
I did not say/mean not to ask them because it might lead to confusion. No, that would be wrong because ontologists need domain experts, and domain knowledge, to create accurate ontologies. Domain experts serve the essential task of (a) providing knowledge, (b) verifying ontological characterizations and ontology content, and (c) quality control...at least ideally!CP> Depending upon what you mean, I'd certainly not ask them to do (b) - at least from an ontological stance.
It's possible that domain experts attempt to identify potential (but not necessarily actual) implicit top-level conceptualizations causes confusion, but not necessarily. What i meant was that because foundational ontological inquiry is so abstract with various concepts either concepts of art (jargon) or vague, the very inquiry itself can lead to confusion, particularly for people not versed in the respective concepts, in the formal analysis, and philosophical ontology. It's like formal logic: people need to be trained in it...FOL, for instance, does not come naturally. Likewise, I suspect, for formalizing top-level aspects. Hence, its easy to get into confusion. The concepts are so vague that a non-ontologist can easily (and rightly in many cases!) ask: "Why are you using that top-level category?", "Why do you define 'object', 'process', '...' that way and not another?", "Why do you say that continuants and occurrents are mutually exclusive?"CP> I'm suspicious of this argument or way of expressing things.CP> It seems to me that you are going about things the wrong way, if the domain experts don't understand the intellectual technology (ontology) why are they being asked to evaluate it? It just sounds as if the team roles have not been thought out.
CP> By the way, the questions are good and need to be answered, just can't see how the domain experts are expected to be the final arbiters.
From an efficiency point of view, if possible, I'd try and do the foundational ontology evaluation before using to build a domain ontology.
But I don't agree that the foundational ontology should be used to build a domain ontology. Domain experts do not necessarily have a particular implicit foundational ontological conceptualization in mind vis-a-vis their domain knowledge. If they do, that can be explicitly formalized into a foundational ontology for that domain ontology. Domain knowledge is acquired and pursued independent of doing formal ontology. So from a more bottom-up approach, look at the domain, develop the onto, and if desired add an upper layer according to this or that criteria, conceptualization, implicit concepts, etc. But maybe I misunderstand what you mean by using the foundational onto to build a domain ontology.
CP> However, I get the feeling you are suggesting that because the domain experts cannot be easily asked to make a choice, that this somehow means that this choice should not be made in the project. If you are suggesting this, I do not see the argument.No, I do not suggest that. I meant that it's not correct that necessarily there is an implicit top-level conceptualization in a domain ontology or in the mind of domain experts. And I meant that ontologists should not try to pull some implicit top-level conceptualization from the minds of the domain experts if there isn't one, nor should they try to coax, convince or impose their own preferred top-level conceptualziation on domain experts. For example, the continuant-occurrent distinction (of a certain interpretation/sense of each category) is something that is often espoused time and again, asserted as being the way the top-level should be, but with little justification or explanation of historical origins. The oft-held mutual exclusivity of the categories is something typically not demonstrated when these dicussions take place (but they should because that has been contested in the literature). Some have questioned the interpretaion and sense of the categories, e.g., the wholly present aspect and other properties of each. The exchange between domain experts and ontologists is of course worth making, but the former may simply not have an implicit top-level in mind, may not agree with the top-level distinctions the ontologist introduces, etc. Also, the danger is that given the specialist knowledge in ontology development, and given domain expert lack of interest in such abstract levels, domain experts may simply accept whatever the ontologist says. This is not correct because they would be blindly accepting the onto commitments, metaphysical assumptions, methodologies, etc. And the consequences of this are that domain expert concepts and objects might be mischaracterized, falsely defined or pidgeonholed into this or that philosophical or methodological theory.CP> It sounds as if you see an essential part of the goal of an ontology project is to get the domain experts to understand and accept the ontology - particularly the foundational aspects. I would not willingly join such a project.
First, I believe it is essential for them to understand the ontology. This will ensure the ontology reflects their domain as accurately as possible, but also helps ensure the ontology is not simply imposing a particular metaphysics, some of which might mischaracterize their domain (hence importance of them understanding the ontology).
Second, they do not have to accept the ontology, but if not then I'd think that would be some cause for changing it. (perhaps analogously to helping a customer with a service).
CP> It also seems to me that you are not using the right tools to assess the ontology - I'm sure you get weird answers if you asked domain experts, particularly those with no understanding of ontology. Why is it essential to assess the ontology in this way?CP> Isn't there a whole tradition that recognises rational reconstruction (Carnap) / regimentation (Quine) changes the meaning of the previously unregimented structure. My guess would be that there is no implicit top-level ontology in the minds of the domain experts, and that introducing it would change the meaning often in ways they do not feel happy with. Isn't this part of the process?
CP> "... , asserted as being the way the top-level should be, but with little justification or explanation of historical origins." I would completely agree this is wrong - it needs to be explained. But I'n not sure the domain experts are the right audience for this.
Michael DeBellis
Dear Michael, some comments.
From: ontolo...@googlegroups.com <ontolog-forum@googlegroups.com> on behalf of Michael DeBellis <mdebe...@gmail.com>
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Styrman, Avril E R
Michael,
you are correct in noting that physics is currently disunified, but we can still identify unified physics as the goal and work towards it. This is important, for physicists are typically very reluctant to even consider postulates by which physics could be unified. We have the circle of stagnation: (1) the current standard postulates raise the need for different parameters for different scales of phenomena; (2) some people introduce different unifying postulates which suffice for all scales, with greatly less auxiliary parameter; (3) these are not accepted because they violate the standard postulates, and we get back to (1). This was noted e.g. by Feyerabend in How to Defend Society Against Science, p. 113:
[E]mpirically minded scientists at once confront it with status quo and announce tri- umphantly that ‘it is not in agreement with facts and received principles’. They are of course right, and even trivially so, but not in the sense intended by them. For at an early stage of development the contradiction only indicates that the old and the new are different and out of phase. It does not show which view is the better one. A judgement of this kind presupposes that the competitors confront each other on equal terms. How shall we proceed in order to bring about such a fair comparison?
This is why we need an evaluation criterion of theories to accelerate the transitions into better theories.
I have defended the principle of economy as an evaluation criterion.
https://www.academia.edu/31591852/ECONOMICAL_UNIFICATION_AS_A_METHOD_OF_PHILOSOPHICAL_ANALYSIS
Cheers,
Avril
Sent: Wednesday, April 26, 2017 11:16:06 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Re: Looking for input regarding Basic Formal Ontology (BFO)
John F Sowa
Your dissertation makes some interesting points. I think that it's
good of its kind. But the failure of the unity of science movement
in the 1930s gave that approach a bad name. Quine and Goodman tried
to revive some of those ideas, but they got nothing of any value.
> physicists are typically very reluctant to even consider postulates
> by which physics could be unified.
https://en.wikipedia.org/wiki/Mathematical_formulation_of_quantum_mechanics
But that gets into some heavy math. For a more elementary and
more intuitive intro, I suggest Chapter 1, pp. 13 to 34, by
Richard Feynman (1965) The Character of Physical Law, MIT Press.
For an excerpt, see the attached file, Feynman_p23.jpg. Note that
each law of physics (or any other science) that makes successful
predictions is accepted as an aspect of reality. Any failure of
such a law leads to a search for new insights -- which lead to
"an avalanche of discoveries".
The crucial terms are insight, intuition, clarity, simplicity, and
elegance. Economy is an attempt to quantify those informal terms.
But it's extremely dependent on the subject matter, the experimental
methods, and the choice of terminology and formalisms. I don't
blame scientists and engineers for having more confidence in their
own intuitions than in some outsider's axioms.
I think that Hilary Putnam (many books and articles) had a better
idea: scientists and engineers are the experts in their domains.
Outsiders (mathematicians, philosophers, and ontologists) can do
good work in helping the experts clarify and formalize their ideas.
But the outsiders must defer to the insights of the experts.
John
Bruce Schuman
AS
We can perhaps survive with disunified science, but our long-term chances are much better with unified science. Even though science is now disunified, this should be seen only as a premature stage. It is not really good philosophy of science to conclude that disunification is desirable, because science is now disunified.
*
I thought it was interesting this morning to hear Donald Trump say he is both a globalist and a nationalist. This is a potent way to think about fundamental polarizations that arise not only in politics or economics but in almost all areas of human thinking. We must think about the whole and the welfare of the whole – and at the same time, we must think about the local or small part contained within that whole – and we most properly should hold these contending forces in balance, rather than push in any one direction over the other (globalism OR nationalism – the whole OR the part – the community OR the individual).
This issue comes up in hundreds of ways in Thomas Friedman’s current book, “Thank You for Being Late”, where he reviews his thesis regarding technological convergence and Moore’s Law, arguing that that we are entering “one the greatest inflection points in history” as “the three largest forces on the planet – technology, globalization and climate change – are all accelerating at once. As a result, so many aspects of our societies, workplaces, and geopolitics are being reshaped and need to be reimagined.” (p3) Friedman cites many specific real-world examples of the mutually influencing interdependency of forces driving this unprecedented kind of social change.
In his introduction to Ch. 6, “Mother Nature”, Friedman talks about “black swans” and “black elephants” (p158). A “black elephant” is a “cross between a black swan – a rare low-probability unanticipated event with enormous ramifications and the elephant in the room: a problem that is widely visible to everyone, yet that no one wants to address, even though we absolutely know that one day it will have vast black-swan-like consequences.”
“Currently there are a herd of environmental black elephants gathering out there – global warming, deforestation, ocean acidification, and mass biodiversity extinction, just to name four. When they hit, we’ll claim that that they were black swans that no one could have predicted, but in fact, they are black elephants, very visible right now – we’re just not dealing with them with the scale and speed that are necessary.”
*
I see potent analogies between the collective human inability to respond to the gathering herd of black elephants and our too-common insistence that “science cannot be unified” – after all, look at previous failures, or 500 examples we can think of. Does this prove that “science” is a vast ocean of semi-independent ad-hoc projects that interconnect in entirely incidental ways – and that unified or integral science is a naïve fantasy? Strict empiricism can easily argue that case.
I like the point that JS made about the relationship of science and engineering. Science is the theory, engineering is the application – and more than that, engineering – actually doing things -- is analogous to the empirical testing that scientific method requires. Theory and fact – abstraction and empiricism – general principle and specific case. These domains are in a fundamental and complementary epistemic relationship that seems common to all human experience. Could we dare postulate some useful general truths about “unified science” in terms this broad?
Pressures on the planet are growing – not only in terms of the four black elephants Friedman cites – but in hundreds of areas of human experience. Yet localists and specialists and “nationalists” far too often resist any sort of global or “whole system” perspective – if on no other grounds than it remains extremely controversial and fundamentally unresolved. True – absolutely – there IS as yet no widely accepted “unified model”. Such a thing many believe is the fantasy of mystics. So – shall we fail to see the stunning interdependent simultaneity of interacting forces across the planet because our most talented and highly trained experts have a narrowly specialized point of view they have been taught is fundamentally incommensurate with other domains?
Seen from a broad perspective, this is just dumb – or should we say “unfortunate” – or “myopic”.
We absolutely need creative visionary leadership on cross-disciplinary integration – solidly grounded in real-world science and engineering, yet guided by high-level general principles that are true across all levels of understanding.
To paraphrase Einstein, ontology without holism is blind – holism without science is weak. Let’s do both. We must have both. Let’s have an ontology that binds disparate elements together into the common frame of human experience.
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Styrman, Avril E R
Sent: Thursday, April 27, 2017 7:11 AM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Re: Looking for input regarding Basic Formal Ontology (BFO)
Michael,
you are correct in noting that physics is currently disunified, but we can still identify unified physics as the goal and work towards it. This is important, for physicists are typically very reluctant to even consider postulates by which physics could be unified. We have the circle of stagnation: (1) the current standard postulates raise the need for different parameters for different scales of phenomena; (2) some people introduce different unifying postulates which suffice for all scales, with greatly less auxiliary parameter; (3) these are not accepted because they violate the standard postulates, and we get back to (1). This was noted e.g. by Feyerabend in How to Defend Society Against Science, p. 113:
[E]mpirically minded scientists at once confront it with status quo and announce tri-umphantly that ‘it is not in agreement with facts and received principles’. They areof course right, and even trivially so, but not in the sense intended by them. For at anearly stage of development the contradiction only indicates that the old and the new aredifferent and out of phase. It does not show which view is the better one. A judgement ofthis kind presupposes that the competitors confront each other on equal terms. How shallwe proceed in order to bring about such a fair comparison?
This is why we need an evaluation criterion of theories to accelerate the transitions into better theories.
I have defended the principle of economy as an evaluation criterion.
https://www.academia.edu/31591852/ECONOMICAL_UNIFICATION_AS_A_METHOD_OF_PHILOSOPHICAL_ANALYSIS
Cheers,
Avril
From: ontolo...@googlegroups.com <ontolo...@googlegroups.com> on behalf of Michael DeBellis <mdebe...@gmail.com>
Sent: Wednesday, April 26, 2017 11:16:06 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Re: Looking for input regarding Basic Formal Ontology (BFO)
>You mean that we do not need unified science, because we can do >work without it? I would rather ask which mode of working is more >progressive.
Its not a question of which one is more "progressive". First of all its not even clear to me what progressive means in that context. But regardless what it means the simple fact is that science right now absolutely is NOT unified and it never has been. The most basic example is physics which is often held up as the model for all the other sciences. But even those guys have two different and fundamentally incompatible models: quantum theory and relativity. And it gets even more non unified as you look at the social sciences and psychology. I took a class a while ago (by a fascinating guy at Berkeley named Terrance Deacon) on Evolution and Human Behavior. He introduced us to all sorts of different models that are used in anthropology and evolutionary psychology: game theory, semiotics, meme theory, information theory, culturgens and more. None of those models are integrated and no sane person would try to integrate them because they are each so full of gaps and holes that we all know that none of them are correct but we hope that some of them are less wrong and worth pursuing.
Another really interesting example is chemistry and physics. For a while there were many people who said that chemistry simply wasn't "real" it was just a way of doing book keeping but the reality was physics. But the deeper they looked into certain problems the more they found they couldn't simply reduce chemical processes to physics ones. By your idealized few of science should they have just given up until they had them integrated? It was only with Linus Pauling's work in understanding how quantum theory and chemistry work together that a true integration of the two was actually achieved.
Michael
On Wed, Apr 26, 2017 at 2:12 AM, Styrman, Avril E R <avril....@helsinki.fi> wrote:
Dear Michael, some comments.
John F Sowa
> our long-term chances are much better with unified science.
> Even though science is now disunified, this should be seen
I agree that value judgments are important, and we should explore
the implications of our decisions and the language about them.
As value judgments, unified and mature sound better than disunified
and premature. But another term for something mature and unified is
"outmoded straitjacket". Then the more attractive value judgments
would be diversity and opportunity.
Carnap and the logical positivists were the chief promoters
of the unified science movement in the 1930s. For a quick
summary of their goals, see Carnap's _Logische Aufbau_ (1928):
> We have repeatedly pointed out that the formation of the
> constructional system as a whole is the task of unified science,
> while construction theory is merely engaged in carrying out the
> appropriate logical investigations. By placing the objects of
> science in one unified constructional system, the different
> “sciences” are at the same time recognized as branches of the
> one science and are themselves brought into a system (§179).
Note that a constructional system is closely related to an ontology.
But another logician, Whitehead (1933) raised a cautionary point:
> Systems, scientific and philosophic, come and go. Each method of
> limited understanding is at length exhausted. In its prime each system
> is a triumphant success: in its decay it is an obstructive nuisance.
For an overview of the many attempts to unify science, see:
https://plato.stanford.edu/entries/scientific-unity/
Following is an excerpt about Paul & Patricia Churchland:
> The most radical form of reduction as replacement is often called
> eliminativism. The position has made a considerable impact in
> philosophy of psychology and philosophy of mind (Churchland 1981;
> Churchland 1986). On this view the vocabulary of the reducing
> theories (neurobiology) eliminates and replaces that of the reduced
> ones (psychology), leaving no substantive relation between them
In the '80s, the Churchlands denigrated traditional psychology with
the prefix "folk-". But neuroscientists today use psychology as
their primary guideline for interpreting what neurons are doing:
> The distinctive feature of brains such as the one we own is their
> uncanny ability to create maps... But when brains make maps, they
> are also creating images, the main currency of our minds. Ultimately,
> consciousness allows us to experience maps as images, to manipulate
> those images, and to apply reasoning to them. (Damasio 2010)
These debates reflect similar debates in the ISO standards committees.
The most successful standards address notations, conventions, and
terminology. In general, any standard that limits or threatens
the substantive *content* of the notation is doomed to failure.
John
Ravi Sharma
- Physical Universe -Knowledge is evolutionary and therefore unification has also to be a continuous effort. Physics is actively in pursuit of this as we discover dark energy, anisotropy in 4degK background cosmic radiation, Higgs Bosons, together with Quarks and Gluons.
- Life - Ranges from Self-knowledge to consciousness - to languages, psychology and neurosciences.
- One needs the Cognizer (s) ( i.e. life) to understand this physical universe and the unification for life requires some form of communication at the levels of life mentioned above. hence the disciplines are somewhat blurred by vocabularies as exemplified by you mainly for life sciences (psychology, neurosciences, etc.).
- It is a riddle that one needs life to understand this physical universe that hopefully does not really depend on current or future forms of life?
- Hence is it that unification of models of this physical universe are somewhat dependent on the unified processes of understanding in life sciences as well??
- Actually understanding is only applicable to life sciences and entities like us, or / and that nature (integral of physical universe and life) already has the required knowledge for future (evolution and destruction)?
John
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Bruce Schuman
Thanks -- and yes to the Hamlet quote. My first thought was "a consummation devoutly to be wished" – hey don’t we just wish we could figure this out in some feasible way….
I actually spent most of yesterday going over these issues, and wrote about 6 bad replies to your brief comments. All bad because impossibly ambitious and necessarily abbreviated. So I thought of Wittgenstein's quote on silence
https://plato.stanford.edu/entries/wittgenstein/
Maybe that’s just good manners. And then there was my thought inspired by the Ramanujan movie I just saw, that described the life of the Hindu mathematician mentored by GH Hardy at Cambridge – who said that he received his ideas directly from the Hindu Goddess Lakshmi (Namagiri) – who somehow transmitted the idea whole to him. Maybe that’s our only hope: direct divine transmission. We’re drowning in too many fragments and facets we know are pertinent. Only the Gods and Goddesses have the psychological bandwidth to put the pieces together.
Right now, I tend to be stumbling through something like the creative process Henri Poincare famously described regarding the night he drank black coffee:
“Every day I seated myself at my work table, stayed an hour or two, tried a great number of combinations, and reached no results. One evening, contrary to my custom, I drank black coffee and could not sleep. Ideas rose in crowds; I felt them collide until pairs interlocked, so to speak, making a stable combination.”
I’m still in that “try great number of combinations” stage – with “ideas rising in crowds” – but that critical pair-lock has not happened in a parsimonious way. So all that remains is verbiage – and this stuff is too stunning for any explication but brief essential algebra.
So, maybe this is the “challenge of holism” – seeing things whole – though not in metaphor but in a true analytic “meronomy” or hierarchic decomposition.
*
For any of you guys (and ladies) with a real interest in creative work, who might want stare at something significantly outside the box and making some rather amazing and perhaps inspiring claims, there is this guy Wai H. Tsang, who studied computer science and neurology at King’s College London, and who has recently put out a book on “The Fractal Brain Theory”.
It’s hard to know what to make of this book, because it is highly detailed and compact, generally well-written and charming, cites hundreds of credible contemporary sources – and makes a big boatload of sweeping and simplifying claims – generally in the form of top-down linear recursion, fractals, and symmetry. It’s guided by a very holistic aesthetic instinct – and is more or less an attempt to smash the illusion of annoying complexity into dust.
I’d like to see “a real scientist” explain why Tsang is off base – without merely imposing mechanistic drudgery on the author, more or less the way that GH Hardy did with Ramanujan. If the guy is a poet-genius of an integral scientific revolution – even if sometimes (or often) speaking in graphic metaphors – I think it’s worth understanding. I bought his book months ago, and yesterday he sent me the entire thing in very good-looking PDF format. This is the introduction.
Bruce Schuman
Santa Barbara California 93101
-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Friday, April 28, 2017 12:59 PM
To: ontolo...@googlegroups.com
Subject: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
On 4/28/2017 11:33 AM, Bruce Schuman wrote:
> our long-term chances are much better with unified science.
> Even though science is now disunified, this should be seen only as a
> premature stage...
> We must think about the whole and the welfare of the whole
Talking about "the welfare of the whole" raises value judgments.
I agree that value judgments are important, and we should explore the implications of our decisions and the language about them.
As value judgments, unified and mature sound better than disunified and premature. But another term for something mature and unified is "outmoded straitjacket". Then the more attractive value judgments would be diversity and opportunity.
Carnap and the logical positivists were the chief promoters of the unified science movement in the 1930s. For a quick summary of their goals, see Carnap's _Logische Aufbau_ (1928):
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Bruce Schuman
This morning, I am going back to Wai H. Tsang's "Fractal Brain Theory" and taking a closer look at its specifics, starting with its introduction. Yes, this book makes some huge and rather stunning and perhaps dismaying claims -- but it presents those claims with what looks to me like real-world documentation and a friendly and courteous professional spirit. This guy is a charming public speaker (he has many videos out there), very quick-spirited, and he's taking on a huge range of interconnected themes in ways that would never be possible within existing or traditional intuitional frameworks.
I want to go over his macro-thesis -- his big-picture vision of cognitive science as he sees the pieces forming a unity. I can't assess the details just yet, but I do see a profound and brilliant and unprecedented integration here -- so I want to slow down, take a closer look, and start itemizing the details.
And I thought it made sense to address John's subject line here:
"Unity or diversity, that is the question. Which is nobler in the mind?"
Seen the right way, this is a powerful and highly germane question—and one that comes up over and over again.
It goes to many related issues like top-down versus bottom-up, part versus whole, or the guiding ethic that might be inherent in an ontology, etc.
Wai H. Tsang in his innocent and brilliant way goes over all this stuff quickly with a light touch -- with strong if brief documentation, and what for me is a persuasive argument.
I bought the JS book on Conceptual Structures in 1984 and was highly influenced by it. I considered it the best book I ever read on mathematical semantics. But I was not a "semantic network" person. I was interested in top-down hierarchical models, and by then had gone a long ways down that path. Still, the highly-intuitive semantic philosophy guiding the JS book laid out a bunch of fundamental principles that influenced everything I did in semantics since then.
I punched forward very hard on my analytic model. I was looking for "a general theory of conceptual form" and – like Wai Tsang -- I wanted a single optimal/integral technology for defining this form.
I followed the universal recursive thesis that "everything is made out of dimensions and dimensions are made out of dimensions". This can get mind-blowing, because it is so stunningly persuasive and every-where present, but seemingly impossible to tame. How or where is this thing grounded? What is that last turtle standing on? No wonder Cantor was hospitalized…
All conceptual form in the abstract can be absolutely defined to n decimal places of accuracy, where every element in the definition is a dimension (as are the number values themselves). But more than this -- the machine-space (or “medium”) supporting the abstraction is defined in dimensions. The alphabet ("terminal characters") from which the words are created is defined in dimensions. The algebraic elements (sets, elements, classes) are defined in dimensions. The fonts that represent the alphabet are defined in dimensions. Every algebraic element is defined in dimensions. Then on top of that, all the definitions and concepts of epistemology are composites constructed from these elements defined in dimensions -- similarity, difference, identity/equality, any form of comparison. All types of variables are defined in terms of their dimensional properties, within a general framework that is constructed from dimensions. Attribute, feature, aspect, factor, property, characteristic -- these are all dimensions (of a composite abstract structure). The range from "quantity" to "quality" is constructed from dimensions, and all "qualities" can be exactly defined (by stipulation) in terms of (intended) quantities. All the major constructions of ontology (taxonomy, meronomy) are built from these elements in a consistent way, serving varying intentions. This is one universally-adaptive general form serving every human intention built from the bottom up in one linear primitive.
***
In the introduction to his book, Wai Tsang introduces his motivation. He was born with a driving instinct to figure out the fundamentals of AI and he recounts some history of this 25-year quest. I pursued a somewhat similar path, and was driven from my undergraduate days by an instinct to disambiguate natural language, since I saw the ambiguity inherent in (any broad) abstraction as the fundamental cause of large-scale human agony. We gotta stop being so stupid -- and implicitly nested semantic ambiguity is the root cause of ruinous disunion (not to mention the bad habits that feed on it). Unlike Wai Tsang, I am less interested in AI per se, and more interested in a universal algebraic semantics. But his approach is seminal, universally inclusive and break-through. I want to follow it and build on it.
In his introduction, Tsang briefly introduces his large-scale vision and goes over two major schools of AI research.
A Single Unifying Structure
Intuitively we know that there must be some sort of unity and integrated structure behind the brain and mind. This is because we know that somehow, all the various myriad aspects of our brains and minds must work together in a unified and coordinated way to achieve our goals and objectives. We know from our experience and introspection that this must be the case, we have this personal sense of oneness and singular wholeness that gives us the impression of self and identity. But it has been very problematic for brain scientists and artificial intelligence researchers to work out how exactly this is the case physiologically and how this may be implemented.
Neuroscience exists as an ocean of facts and findings, with no obvious way to fit them all into a unified understanding or single cohesive and coherent structure. The Fractal Brain Theory introduces a very elegant way of arranging all the various aspects of brain and mind, fitting them all together into a single top-down hierarchical classification structure. This partly derives from having a single unifying language with which to describe everything in the first place. Having a common description for all the separate pieces of the puzzle, is the prerequisite for fitting all the pieces together into a single unifying structure.
Furthermore this unified classification structure also derives from what we know about hierarchical representations and relationships in the brain as suggested by the actual neurophysiological substrate and experimental findings. This gives us a very powerfully integrated and all encompassing overview of brain organization, together with the emergent structures of the mind.
It is an important stepping stone to fully understanding the brain and the creation of true artificial intelligence. After all, many of the biggest names in AI and theoretical neuroscience stress the importance of hierarchical structures, representations and processes. What the Fractal Brain Theory is able to show is that the entirety of brain and mind may be conceptualized as a single tightly integrated and all encompassing hierarchical structure. A Carnegie Mellon University AI researcher Tom Mitchell thinks in relation to creating AI that, ‘it is not obvious to me that we are missing [AI] components.’ but he thinks what is missing is that, ‘we don’t have a good architecture to assemble the [existing AI] ideas.’ So on one level this is something which is provided by the Fractal Brain Theory, exactly the sort of framework that is needed for the integration of the various conceptions of AI as well as that of the mind sciences in general.
The single all encompassing structure of brain and mind in turn leads to the third and most dramatic breakthrough which the Fractal Brain Theory delivers. Given our all encompassing unifying structure we may then ask, is it possible to define a single overarching process over that structure which captures all the separate processes happening within it. Or put another way, if we can represent the entire brain and mind as a single integrated data structure, then is it possible to specify a single algorithm over that data structure, which captures the functionality of all the partial algorithms of brain and mind? And the answer is yes.
A Single Unifying Process and Critical Algorithm
This is the most surprising and perhaps even shocking property of the fractal brain theory. Because it shows that there exists a stunning simplicity behind the inscrutable and mysterious functioning of the brain and mind. The Fractal Brain theory shows how a single unifying recursive process is able to explain all the component sub-processes of brain and mind.
Putting this powerful idea into the context of what some of the leading researchers in the fields of artificial intelligence and theoretical brain science are currently thinking; roughly speaking we have two camps. On one side we have those thinkers who think that underlying the brain and mind is some sort of unifying and ultimately relatively simple answer waiting to be discovered. This viewpoint goes hand in hand with the notion of some critical breakthrough or the elucidation of a set of basic principles which will unlock the puzzle of brain and mind which will then enable the creation of true AI. On the other side we have those thinkers who believe the opposite, that this won’t be the case. So this idea of a critical algorithm and unifying process has already been anticipated to some extent by various researchers in the mind and brain sciences. We’ll discuss this camp first.
For instance Eric Horvitz the head of AI research at Microsoft, has speculated that there may exist a ‘deep theory’ 31 of mind waiting to be demonstrated. Sir Steve Grand who is a prominent British AI theorist and inventor, thinks there may exist a ‘single sentence solution’ 32 behind how the brain works and which would provide the key to creating AI. Several prominent AI and brain researchers such a Jeff Hawkins, Ray Kurzweil (A successful AI implementer and a godfather of the Technological Singularity) and Andrew Ng (Former director of the Stanford AI lab and now head of AI research for Baidu Corp); all believe that there may exist a universal ‘cortical algorithm’ which captures the functionality of all the various different areas of cerebral cortex which together with the related underlying wiring comprises over 80% of the human brain. And we’ve already mentioned Pedros Domingos and his ideas for a Master Algorithm or ‘a grand unified theory of machine learning, akin to the standard model of physics’.
The second camp is represented by researchers like Ben Geortzel who doesn’t believe in the existence of a critical algorithm that could give rise to true AI, saying ‘I don’t think there’s any one algorithm that’s critical to intelligence’ 33. Nils Nilsson who was the director of SRI (Stanford research institute) AI Lab and author of many books on the subject, ‘doubts’ that an ‘overarching theory of AI will ever emerge’. Danny Hillis who did pioneering work on massive parallel computers expressed the view that ‘Intelligence is not a unitary thing’, but rather a collection of rather ad hoc solutions. Marvin Minsky and Doug Lenat both prominent practitioners of the so called GOFAI or ‘good old fashioned AI’, which involves mainly language and symbolic processing; have expressed similar sentiments. Minsky believes that the brain is made up of multiple functional modules that have evolved separately to produce a multitude of different algorithms, what he has called a ‘society of mind’. He has explicitly stated that, ‘My conclusion is that there isn’t any general principle of how people think’. Lenat’s work holds out to the hope that AI or at least ‘common sense’ for AI will emerge from the collecting together and human hand coding of a myriad number of facts and pieces of knowledge. And then there’s Stephen Wolfram, the creator of Mathematica, who said at the 2011 Singularity Summit, ‘When I was younger I used to think that there would some great idea, some core break through that would suddenly give us Artificial intelligence.’ But now he doesn’t anymore.
This is “the great split” – the continental divide of cognitive science – the “unified or the diversified” -- and goes directly to the old classification of “scruffies” (bottom-up empirically-minded heuristic thinkers without grand integration or good mutual compatibility) and “neats” (pure-minded system theorists who want everything to fit into one internally-consistent framework defined under strict parsimony in all things).
Unity or diversity – that is the question. Which is nobler in the mind?
So, says the Wizard – let’s do a both/and – and explain why. Nationalism, globalism, part, whole, bottom-up, top-down, immediate practicality or grand scheme – maybe we need a “golden spike” to nail together our intercontinental railway that spans these huge and ultimately all-inclusive domains.
Here’s the Fractal Brain thesis in a sentence:
The Fractal Brain theory shows how a single unifying recursive process is able to explain all the component sub-processes of brain and mind.
I started seeing something very much like this when I was an undergraduate at UC Santa Cruz, and I drew a thousand diagrams trying to figure it out. Though I do tend to be a compulsive top-down “neat”, maybe my instinct for the atomization of semantic space and absolutely all its constructive elements gives me an ultimately bottom-up approach to this visionary all-inclusive integration. We can build everything from nothing, with pure linear recursion and one primitive element.
I think we need network space to examine these possibilities in high detail. The world is in a dangerous (and stupid and increasingly “unreal”) place. We need a massive infusion of whole-systems visionary thinking, pulled out of this endless and fruitless bottom-up/top-down debate. Let’s not demand academic micro-fragmentation in an initial thesis. Let’s get the big picture on the table in a way we can see all the pieces and push them around to make them fit. Argue any case you want. But don’t kick over the table. Wai Tsang has given us a way to do this.
Bruce Schuman
Santa Barbara California 93101
-----Original Message-----
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of John F Sowa
Sent: Friday, April 28, 2017 12:59 PM
To: ontolo...@googlegroups.com
Subject: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
On 4/28/2017 11:33 AM, Bruce Schuman wrote:
> our long-term chances are much better with unified science.
> Even though science is now disunified, this should be seen only as a
> premature stage...
> We must think about the whole and the welfare of the whole
Talking about "the welfare of the whole" raises value judgments.
Gregg Reynolds
Intuitively we know that there must be some sort of unity and integrated structure behind the brain and mind. This is because we know that somehow, all the various myriad aspects of our brains and minds must work together in a unified and coordinated way to achieve our goals and objectives. We know from our experience and introspection that this must be the case, we have this personal sense of oneness and singular wholeness that gives us the impression of self and identity.
Bruce Schuman
Are you able to walk a straight line? Compose a coherent sentence?
A thousand or 100,000 individually distinguishable “parts” within you combine to work together “as one” to support those intentions. That is “linear chunking” to the max.
So, you get one vote in this huge debate. Thanks.
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Gregg Reynolds
Sent: Monday, May 1, 2017 1:14 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
On May 1, 2017 2:49 PM, "Bruce Schuman" <bruces...@cox.net> wrote:
Intuitively we know that there must be some sort of unity and integrated structure behind the brain and mind. This is because we know that somehow, all the various myriad aspects of our brains and minds must work together in a unified and coordinated way to achieve our goals and objectives. We know from our experience and introspection that this must be the case, we have this personal sense of oneness and singular wholeness that gives us the impression of self and identity.
Preposterous on the face of it. Ask John Nash, among countless others whose "personal sense" may be that the world - and the self - is chaotic. Not to mention many religions. Multiplicity seems much more likely to me.
Beware of scientists pushing The One True Theory.
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Rich Cooper
Greg, you wrote:
Beware of scientists pushing The One True Theory.
I agree, but its innate human practice.
Bruce,
Both unity and diversity are required. Science is a struggle of basic ideas for shares of subscribers among the "scientific" community. For every great idea, there are a million misleading ones. But to get rid of the misleading ones leads to stagnation. For every error in one theory, fixing it helps produce new ideas through new experiences.
Storing and evaluating new experiences leads to more choice, and usually therefore more effective actions and objects. At least, that is the position of case based reasoning advocates. And of course, each object and its properties and values can be situation dependent, in which case I prefer the IDEF0 activity model as a way to express those changes, communicate them to others, and build a database of experiences that can be used in training solutions.
Here is a better description in depth of how to use IDEF0 (or another model) in AND/OR search graphs with parameterized functions:
http://englishlogickernel.com/Patent-7-209-923-B1.pdf
Sincerely,
Rich Cooper,
Rich Cooper,
Chief Technology Officer,
MetaSemantics Corporation
MetaSemantics AT EnglishLogicKernel DOT com
( 9 4 9 ) 5 2 5-5 7 1 2
Michael DeBellis
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Gregg Reynolds
I just want to clarify what my position on all this is. I agree with the people who say that unified science is better than non-unified science.
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Gregg Reynolds
Are you able to walk a straight line?
Compose a coherent sentence?
A thousand or 100,000 individually distinguishable “parts” within you combine to work together “as one” to support those intentions. That is “linear chunking” to the max.
So, you get one vote in this huge debate. Thanks.
Ravi Sharma
Bruce, John
Thanks for this thread somewhat going beyond Ontology.....
Understanding Knowledge in the living - Life Sciences
Great extracts from Tsang's book. Obviously, the great scholar has intensively studied and synthesized the AI aspects of Nature Especially Life recursively self-learning and managing. I will buy, read the book and comment on it in-depth.
Tsang says what John Sowa said / your post said earlier.
"The path I took instead was that I saw neuroscience and psychology - the understanding of the human brain and human behaviour - as the real key to creating truly intelligent machines."
Difference between mind and brain is more than understanding the physiology of brain processes alone!
Mind is akin to Sanskrit Word Manas or Manah (nearly similar but not exactly same as mind) which is the subject of 4-5 millennia’s work and Manas is the central force that makes life do good or bad or any actions. Brain alone does not until motivated by Manas to connect to Senses and Action. It is a layer above "breathing" or life sustenance but below knowledge, understanding and certainly below self-knowledge. What external factors modify this self- knowledge in the evolution is the key question, Tsang says ontognesis and neurogenesis.
Ontogenesis is to be understood by me further by studying Tsang and referenced works.
"It is not so obvious, but taken as fact now due to advances in molecular biology, that the genome modifies itself using what are known as ‘epigenetic’ mechanisms which alter the algorithmic functioning of the DNA contained in the genome. These pre-programmed epigenetic modifications are repeated recursively in the course of ontogenesis and neurogenesis."
If pre-programmed, then epigenetic processes will lead to deterministic future in evolution?
I proposed experiments for mammalian mutation on the space station in microgravity environment, hypothesizing that gravity or its absence (micro-gravity) could be mutation inducing parameter if studied over 100+ generations of Rats bred in space and earth as well as in combinations such as few generations in space and then few on Earth etc.!
Some scientists think that nature does not know it all but responds to situation but by physical laws. Life is sparse in this universe and even if we agree with Tsang, what about non-living part of Universe?
Ancient Indo-European thinking in one model hypothesizes universal consciousness permeating the living and non-living and that both matter-energy as well as life have a begin-end cycle. This is not inconsistent with physics, especially for single universe or big bang!
Ontology would address itself at-least with how these aspects and entities and relationships work for example at neural, epigenetic, genetic and Unified (standard - including Lambda term of Einstein) model of Physics and of course how to handle uncertainties, incorporation of new knowledge etc.
This boils-down to deepest in metaphysics, does the Universe as manifested need any external influence in its working or is it a closed loop yet self-transforming system?
Now we briefly discuss the process of discovery (ours only, as nature has gravity from beginning and not only after discovery of Gravity, or after Newton).
Einstein described to his Son - in - law, how he understood Gravity - describing preexisting dejection state of mind -futility of hard work (similar to your Quote on Poincare) and going to bed thinking that his life's effort is wasted, but then having a vision and when he got up the pieces of puzzle fell into a mosaic completing the picture and even 100+ years later we have just come around to understanding and expanding on his general relativity discovery still largely using the indeterminate Lambda in his equations.
If we can understand this process, may be AI as well as some of us can hope to help understand knowledge?
Rest in next mail.
PS: I also saw The man who knew infinity on Ramanujan - intrigue among the Deductive Processes taught to Ramanujan by Prof. Hardy and the Intuitive Visualization of solutions directly by Ramanujan by meditating (helped by Namagiri - Icon). Also, authentically recreated real historic backdrop of war era and difficulties of Prof. Hardy to convince colleagues in UK of Ramanujan's Genius!
Regards.
Thanks -- and yes to the Hamlet quote. My first thought was "a consummation devoutly to be wished" – hey don’t we just wish we could figure this out in some feasible way….
I actually spent most of yesterday going over these issues, and wrote about 6 bad replies to your brief comments. All bad because impossibly ambitious and necessarily abbreviated. So I thought of Wittgenstein's quote on silence
https://plato.stanford.edu/entries/wittgenstein/
Maybe that’s just good manners. And then there was my thought inspired by the Ramanujan movie I just saw, that described the life of the Hindu mathematician mentored by GH Hardy at Cambridge – who said that he received his ideas directly from the Hindu Goddess Lakshmi (Namagiri) – who somehow transmitted the idea whole to him. Maybe that’s our only hope: direct divine transmission. We’re drowning in too many fragments and facets we know are pertinent. Only the Gods and Goddesses have the psychological bandwidth to put the pieces together.
Right now, I tend to be stumbling through something like the creative process Henri Poincare famously described regarding the night he drank black coffee:
“Every day I seated myself at my work table, stayed an hour or two, tried a great number of combinations, and reached no results. One evening, contrary to my custom, I drank black coffee and could not sleep. Ideas rose in crowds; I felt them collide until pairs interlocked, so to speak, making a stable combination.”
I’m still in that “try great number of combinations” stage – with “ideas rising in crowds” – but that critical pair-lock has not happened in a parsimonious way. So all that remains is verbiage – and this stuff is too stunning for any explication but brief essential algebra.
So, maybe this is the “challenge of holism” – seeing things whole – though not in metaphor but in a true analytic “meronomy” or hierarchic decomposition.
*
For any of you guys (and ladies) with a real interest in creative work, who might want stare at something significantly outside the box and making some rather amazing and perhaps inspiring claims, there is this guy Wai H. Tsang, who studied computer science and neurology at King’s College London, and who has recently put out a book on “The Fractal Brain Theory”.
It’s hard to know what to make of this book, because it is highly detailed and compact, generally well-written and charming, cites hundreds of credible contemporary sources – and makes a big boatload of sweeping and simplifying claims – generally in the form of top-down linear recursion, fractals, and symmetry. It’s guided by a very holistic aesthetic instinct – and is more or less an attempt to smash the illusion of annoying complexity into dust.
I’d like to see “a real scientist” explain why Tsang is off base – without merely imposing mechanistic drudgery on the author, more or less the way that GH Hardy did with Ramanujan. If the guy is a poet-genius of an integral scientific revolution – even if sometimes (or often) speaking in graphic metaphors – I think it’s worth understanding. I bought his book months ago, and yesterday he sent me the entire thing in very good-looking PDF format. This is the introduction.
http://www.iawwai.com/FractalBrainTheory.html
Bruce Schuman
Santa Barbara California 93101
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Edward Barkmeyer
Michael DeBellis wrote:
> So given that physicists (and other scientists) don't currently have one unified model of science it seems to me to make no sense to require some unified model as the basis for *all* our ontologies. [emphasis mine]
I completely agree.
On the other hand, the purpose of an AI “ontology” is to enable the production of useful results by automated reasoning in a given problem space. This AI approach is particularly useful for dealing with problem spaces in which no individual contributing expert has a complete understanding of the space, and thus the views, or at least the observations, of several expert contributors must be reconciled. That reconciliation demands a unified model of the problem space, because the alternative is some intrinsic contradiction, however subtle.
The breadth of that unification need only be great enough to cover the purpose of the ontology with respect to the problem space. So we do not need “one unified ontology as the basis for all models”. But it is not atypical to find that the required breadth and depth of the ontology for a problem space is rather larger than any individual expert expects, and thus the purpose-built ontology ends up addressing some set of “fundamental concerns”. And when an existing upper ontology (a unifying theory) addresses those concerns adequately, it is a useful resource.
It is my impression, possibly ill-informed, that the progression of unification in scientific theory has come of exactly the same problem: reconciling multiple theories that explain, and *correctly predict*, diverse observations in an area of interest. Per Einstein:
"The world we have made as a result of the level of thinking we have done this far creates problems that we cannot solve at the level of thinking at which we created them."
So the reason why we don’t care about unifying paleontology and astrophysics is that we have not yet encountered/created a problem space in which we need to do so.
-Ed
Ed Barkmeyer
Thematix Partners
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Michael DeBellis
Sent: Monday, May 1, 2017 6:03 PM
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Bruce Schuman
Thanks, Michael. I looked up your background the other day. I appreciate the comments.
The way I would put this is – we are not really suggesting that “monolithic science” is somehow a good idea – where “everybody agrees on everything”.
That would be 1) impossible; 2) very static and dead and non-creative; and 3) to quote Gregg Reynold, preposterous.
What we are looking for is not precise agreement on details – but more or less something like loose creative agreement on methods and objectives and ways to cross borders and boundaries.
What I personally would like to see happen – what I personally regard as something like absolute scientific apocalypse – is an integral/optimal general theory of conceptual form.
I think there IS such a thing – and the reason we know it’s “the best” is because it is the most parsimonious – fewest possible elements (1), fastest possible flow.
*
The way I see it – all science is defined in concepts. As John Sowa has pointed out many times, there is no one general best theory of concepts – at least not yet. So some of us are pushing that way.
I bought a great book JS wrote on concepts published in 1984.
I have another great book on concepts, also published in 1984, with the title “On Conceptual Modelling: Perspectives from Artificial Intelligence, Databases, and Programming Languages”. I had to laugh – and the phrase was burned into my mind in a way that I remembered for twenty years that enabled me to re-locate this book and buy a copy recently – “semantic networks – those creatures of darkness” I lost that book fifteen years ago or more, and purchased a perfect copy recently because I remembered that phase over all the years and Amazon had an immaculate used copy from Colgate University.
This is a heavy-hitting top-of-the-line computer science book that brings together all these perspectives.
This is one of the great things about the ontolog forum – it brings together guys who were around when computer science was being born – guys that were at major research labs or places like Xerox Parc
Personally, I think there was a great general vision driving that growth – and people could see it – and right about 1984 or the mid-1980’s, that creative vision was sparking high. John’s book came out of that creative period. Yesterday, I repurchased the October 1987 special edition of Scientific American Magazine on “Computer Revolution” that goes over a lot of that. Great article by David Gerlernter on parallel computing – he’s the guy from Yale who was badly injured by the Unibomber…
But since those days – the stunning growth of computer power has – in my opinion – somewhat eclipsed the clarity of vision that was driving those earlier days. It’s made things muddy, and made the math extremely heuristic.
Personally, I think one hugely obscuring factor for the creative intellect was the (get this) emergence of proportional fonts. In the early days we couldn’t afford them. Now everybody assumes they are cool and essential.
John Sowa and many others come out of the days of pure text emails and email programs like Pine – where the page was a 100% linear/square matrix, and you could get a really clear sense of the matrix structure of language. Back in those days, in many ways “a typewriter was isomorphic to a computer”
Both had a linear/square rigidly-defined matrix structure page (screen) – with implicit rows and columns, like graph paper -- and a finite alphabet and a finite keyboard. Every keystroke from a typewriter landed in just one square of that matrix, which contained either one element (terminal character) from that alphabet, or nothing.
Just feeling your way into that isomorphism, you could envision the linear/matrix structure of symbolic representation. This kind of thing was driving a lot of the inspired creativity of Douglas Hofstadter (Goedel/Escher/Bach, Metamagical Themas). He wrote fascinating stuff on recursion and the data structure of LISP.
Today – that sense of rigid matrix is gone – because of near-continuous variability on the screen. You just can’t “see” straight through the keyboard into the depths of the operating system the way you could when machines were much simpler and lower-capacity.
But for me, inspired by those days – and still stuck there in many ways – the power we were seeing then is still the driving edge of the revolution, and maybe more essential today than ever.
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Michael DeBellis
Sent: Monday, May 1, 2017 3:03 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
I just want to clarify what my position on all this is. I agree with the people who say that unified science is better than non-unified science. That's why unifying quantum theory and relativity is such a hot topic. Its why Pauling's work unifying chemistry and quantum theory is so important.
My point is that the science we have now is clearly not unified as illustrated again by quantum theory and relativity (although I could go on at length with examples from other disciplines). What's more scientists don't seem to care that its not unified and have been making good progress with non-unified models.
So given that physicists (and other scientists) don't currently have one unified model of science it seems to me to make no sense to require some unified model as the basis for all our ontologies. Not only is such a requirement not realistic (how can ontologists solve a problem that physicists can't?) it is bound to lead us down dead ends where we do arm chair philosophy to develop unified models based on nothing more than our intuitions.
Michael
On Mon, May 1, 2017 at 12:49 PM, Bruce Schuman <bruces...@cox.net> wrote:
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Obrst, Leo J.
Genius and crackpottery are often indistinguishable. This reminded me of Hofstadter’s Butterfly: http://www.nature.com/news/physicists-net-fractal-butterfly-1.13717,
See also: http://www.brandeis.edu/magazine/2015/winter/featured-stories/crackpottery.html.
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com]
On Behalf Of Bruce Schuman
Sent: Sunday, April 30, 2017 2:40 PM
To: ontolo...@googlegroups.com
Bruce Schuman
(laugh) – Well, maybe we got to “crack the pot” to get “outside the box”
Which reminds me of Leonard Cohen’s song Anthem – with the line “there’s a crack in everything, that’s how the light gets in….”
https://www.youtube.com/watch?v=6wRYjtvIYK0
Personally, I want to see some bold holistic adventurer tack his thesis to the door, then go gather the illuminati to kick it around to see if they can make it work better….
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Obrst, Leo J.
Sent: Tuesday, May 2, 2017 7:30 AM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
Genius and crackpottery are often indistinguishable. This reminded me of Hofstadter’s Butterfly: http://www.nature.com/news/physicists-net-fractal-butterfly-1.13717,
See also: http://www.brandeis.edu/magazine/2015/winter/featured-stories/crackpottery.html.
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Bruce Schuman
Sent: Sunday, April 30, 2017 2:40 PM
To: ontolo...@googlegroups.com
Pat Hayes
On May 2, 2017, at 9:29 AM, Obrst, Leo J. <lob...@mitre.org> wrote:The Fractal Brain Theory
Bruce Schuman
Ah yes, circular recursion – a conversation about itself that can lead to serious digestive problems…
Bruce Schuman
Santa Barbara California 93101
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Gary Berg-Cross
terminology. In general, any standard that limits or threatens
the substantive *content* of the notation is doomed to failure.
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Joel Luís Carbonera
Bruce Schuman
This is a succinct and very clarifying answer. Very reasonable, and thank you.
The purpose of an AI “ontology” is to enable the production of useful results by automated reasoning in a given problem space. This AI approach is particularly useful for dealing with problem spaces in which no individual contributing expert has a complete understanding of the space, and thus the views, or at least the observations, of several expert contributors must be reconciled. That reconciliation demands a unified model of the problem space, because the alternative is some intrinsic contradiction, however subtle.
The breadth of that unification need only be great enough to cover the purpose of the ontology with respect to the problem space. So we do not need “one unified ontology as the basis for all models”. But it is not atypical to find that the required breadth and depth of the ontology for a problem space is rather larger than any individual expert expects, and thus the purpose-built ontology ends up addressing some set of “fundamental concerns”. And when an existing upper ontology (a unifying theory) addresses those concerns adequately, it is a useful resource. . . .
So the reason why we don’t care about unifying paleontology and astrophysics is that we have not yet encountered/created a problem space in which we need to do so.
Well, suppose the “sciences” that might demand some common ontology were ecology and economics and the “problem space” was the United States Congress. There’s a space where these issues are crashing into one another with something close to deadly force and the creative problem-solving has been in paralytic gridlock for at least 8 years.
So maybe then the question becomes “who’s going to take on this huge job” – and maybe the answer is some major engineering firm with expertise in large-scale system engineering – like Mitre or Rand
https://www.mitre.org/capabilities/systems-engineering/overview
https://www.mitre.org/sites/default/files/publications/se-guide-book-interactive.pdf
For implementation, the prime contractor could partner with the Bridge Alliance, already developing a national network of non-profits and academic groups working in this direction.
For large-scale activation – consider the growth of Facebook – now approaching 2 billion users.
The world is so ready for this, the entire concept is now starting to look like low-hanging fruit….
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Edward Barkmeyer
Sent: Monday, May 1, 2017 4:35 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
Michael DeBellis wrote:
> So given that physicists (and other scientists) don't currently have one unified model of science it seems to me to make no sense to require some unified model as the basis for *all* our ontologies. [emphasis mine]
I completely agree.
On the other hand, the purpose of an AI “ontology” is to enable the production of useful results by automated reasoning in a given problem space. This AI approach is particularly useful for dealing with problem spaces in which no individual contributing expert has a complete understanding of the space, and thus the views, or at least the observations, of several expert contributors must be reconciled. That reconciliation demands a unified model of the problem space, because the alternative is some intrinsic contradiction, however subtle.
The breadth of that unification need only be great enough to cover the purpose of the ontology with respect to the problem space. So we do not need “one unified ontology as the basis for all models”. But it is not atypical to find that the required breadth and depth of the ontology for a problem space is rather larger than any individual expert expects, and thus the purpose-built ontology ends up addressing some set of “fundamental concerns”. And when an existing upper ontology (a unifying theory) addresses those concerns adequately, it is a useful resource.
It is my impression, possibly ill-informed, that the progression of unification in scientific theory has come of exactly the same problem: reconciling multiple theories that explain, and *correctly predict*, diverse observations in an area of interest. Per Einstein:
"The world we have made as a result of the level of thinking we have done this far creates problems that we cannot solve at the level of thinking at which we created them."
So the reason why we don’t care about unifying paleontology and astrophysics is that we have not yet encountered/created a problem space in which we need to do so.
-Ed
Ed Barkmeyer
Thematix Partners
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Obrst, Leo J.
The problem with Congress is not the need for some consolidated ecology + economics science or ontology, but the need for a political and sociological values readjustment. This could include deprecating the vast input of money into campaigns (more and more of which is dark money), turning “gerrymandering” over to independent, non-partisan politically external groups, a stronger press and a citizenry more inclined to understand truth and seek it, etc.
Thanks,
Leo
Styrman, Avril E R
Hi all,
I summarized some comments. Most seem to agree that unification is better than disunification, because unification is progressive. This is the central point: if progress is the goal, then there are no good reasons to somehow try to prevent it or avoid it; but the case is different if holding on to the tradition is the goal.
Bruce Schuman:
We absolutely need creative visionary leadership on cross-disciplinary integration – solidly grounded in real-world science and engineering, yet guided by high-level general principles that are true across all levels of understanding.
Michael DeBellis:
I agree with the people who say that unified science is better than non-unified science.
Gregg Reynolds:
why? what makes one better than the other? the only thing that really matters is that science "works". whether it is monolithic or pluralistic is irrelevant - a matter of ideological hand-waving. does anybody really care if we do or do not have a theory that "unifies", say, paleontology and astrophysics?
Joel Luís Carbonera
Because the unification would provide the relationships between aspects that now are seem as separate ones. Maybe they are just partial views of the same phenomenon. And, if we could see the relations between these aspects, probably we could explore a whole new set of technologies that take advance of them.
Ed Barkmeyer
So the reason why we don’t care about unifying paleontology and astrophysics is that we have not yet encountered/created a problem space in which we need to do so.
Some are not totally convinced.
John Sowa
But the failure of the unity of science movement in the 1930s gave that approach a bad name.
Do not get distracted from the main lines:
1. We would be better off with unified science
2. The project of unification failed in the early 20th century
3. As a result of the failure, nowadays unification has a bad name
4. What that failure should be taken to indicate is that theories put forth in the early 20th century have failed, not that unification is a failed project
JS:
I think that Hilary Putnam (many books and articles) had a better idea: scientists and engineers are the experts in their domains. Outsiders (mathematicians, philosophers, and ontologists) can do good work in helping the experts clarify and formalize their ideas. But the outsiders must defer to the insights of the experts.
You seem to suggest that we are already in the hold of the correct basic postulates, and the rest is a matter of working with them. This approch cannot resolve the problem of disunification that results exactly from the contemporary standard basic postulates, above all the relativity principle, constancy of the velocity of light and the equivalence principle. Moreover, all these should be seen as parameters that had to be added on the top of Newtonian physics that is based on force. For a real change, we must go further back and replace force by energy. It is always like this: whatever the paradigm is, there are people who oppose it. This underlines the importance of economy as the criterion: we do not have to take all suggestions seriously, but we should take objectively better alternatives seriously, if progress is the goal. We can only introduce alternatives and evaluate them.
Michael DeBellis
So given that physicists (and other scientists) don't currently have one unified model of science it seems to me to make no sense to require some unified model as the basis for all our ontologies. Not only is such a requirement not realistic (how can ontologists solve a problem that physicists can't?) it is bound to lead us down dead ends where we do arm chair philosophy to develop unified models based on nothing more than our intuitions.
The reason why physics remains disunified is that mainstream physicists do not want to give up theories they have grown familiar with. Armchair philosophy is not an issue here, for we have physicists who have developed objectively better models of physics than the standard model (=simpler, understandable, paradox-free). The greatest challenge is stagnation. Many people seem to believe that scientists are like angels. Unfortunately this is not the case; Feyerabend is much closer to the truth. To illustrate, in a conference ball, a physics professor suggested this line of thought:
1. Physics is an open enterprise and physicists are objective people, ready to welcome new suggestions and theories that work
2. If your theory indeed were good, it would have been noticed already by the physics community
3. As it remains unnoticed by the community, it cannot be good
Cheers,
Avril
Bruce Schuman
Yes, you are so right, thank you. In my enthusiasm for the grand scheme I left out a critical piece – which presumes that an inclusive ontology – perhaps of the type I described (economy/ecology) -- can and should and probably must contain an innately guiding ethical principle – a “value system”. This influence would probably reside at “the top” (as in “upper ontology”) – up where we might place “the one” or “the whole” or “oneness” – or in some models, “God”. So the general form of the ethic would become something like “every decision at every level made with respect to the whole.”
What I want to see in a revitalized democracy (where we address the issues you raised and many others) is a recursive nesting of levels of governance – where at any point in a descending cascade, every collective decision (where 2 or more people form some governing judgment that affects them all), there is a kind of “co-creative convergence” process, where both or all parties are responsive to all the information brought into the decision context.
The idea that has begun to possess me on this theme of optimal collective decision-making is some notion of convergence toward this recursive multi-level center from every point in some local but networked context. So, if we see society as ideally democratic at every level of scale – the family at the dinner table, the local neighborhood association, the city council, county and state and regional government, national and global governance, etc. – the really powerful holistic model is defined around this concept of “center everywhere”. It’s not “top down” and it’s not “bottom up.” Instead, everything is ruled from or by the center – guided by the center – because through this framework, not only is everything balanced locally but every decision is made with respect to and in the context of the whole. This should nest the local perfectly into the context of the global, in a correct balance of independence and dependence. Every point in the grid has the same level of authority, and is authenticated in the same way.
This model is essentially fractal along descending levels of scale, with every level connected to every other level, and everything interdependent – like a “mobile” hanging from a common axial center-point, with all levels held in one balance. This become an integral system with an innate ethic built-in – and which, it seems to me, could achieve an amazing integrity by following this notion of center everywhere (like the old mystical phrase). Whereas today our culture is fragmented and divided at almost every point, in this framework all levels of social organization are held together through an identical common point that is located at every level of scale – and could be understood to reside within the individual as the bottom-level replication of this common center-point. This process reverses the polarity of “every point a point of division” to “every point a point of convergence”.
The objective at the local point of decision is to define a balance between all immediately contributing elements – like the scales of justice in law – or the process of homeostasis in a living body. Every level of scale, including the individual, has its own innate center-point of balance – ranging up the levels of scale, and connecting to every level of scale above and beneath, always through center-point. The idea of “center everywhere” – is something like “it’s always the same center, no matter the level of scale” – and because that is true – there is an absolute “through line” (a “plumb line for true judgment”) that extends directly through common center-point to every decision-point in the grid. The local decision is thereby always defined in the context of the whole – and can always balance the fundamental social tension of individual (“the part” – diversity ) versus the community (“the whole” – unity). In this way, “law” does not have to be defined in broad categories that always end up being wrong or unbalanced in some specific cases, due to differences in local context. Instead, law becomes highly context-sensitive, and can make decision on a case-by-case basis without losing integrity. Approached this way, a critical and very difficult issue like abortion is not approached in the same way in every case.
This kind of model does involves a kind of moral/ethical conversion at every point – but only in small/incremental ways – everybody moves a tiny increment towards common center -- and you get a whole-systems effect kind of like the Simpson-Bowles amendment (“everybody’s ox gets slightly gored” – nobody gets everything they want, but “the whole” is optimized – and, we hope, the rising tide lifts all boats).
This kind of recursive chaining proposes a direct line of connection from “the local point” – something like “the infinitesimal” (the individual) -- to the center of the global whole – “the infinite” (everybody) – and proposes something like an optimal decision criteria “for everything” – based on alignment with that central master vector that optimally aligns everything in balance, towards which supposedly all decisions should incrementally converge….
**
Just a vision for a networked society – but yes, definitely – we need an ontology with an ethic – an intuitive ethic consistent with the best any successful society throughout history has ever brought to this question….
Bruce Schuman
Santa Barbara California 93101
From: ontolo...@googlegroups.com [mailto:ontolo...@googlegroups.com] On Behalf Of Obrst, Leo J.
Sent: Thursday, May 4, 2017 1:21 PM
To: ontolo...@googlegroups.com
Subject: RE: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
The problem with Congress is not the need for some consolidated ecology + economics science or ontology, but the need for a political and sociological values readjustment. This could include deprecating the vast input of money into campaigns (more and more of which is dark money), turning “gerrymandering” over to independent, non-partisan politically external groups, a stronger press and a citizenry more inclined to understand truth and seek it, etc.
Thanks,
Leo
John F Sowa
I would never try to prevent or avoid unification.
> This is the central point: if progress is the goal, then there
> are no good reasons to somehow try to prevent it or avoid it;
"unity or diversity" is inclusive: Both are possible and desirable.
But the major question is "How?"
> Some are not totally convinced.
>
> John Sowa
> But the failure of the unity of science movement in the 1930s
> gave that approach a bad name.
diversity, and progress. Unfortunately, those are three vague terms.
In each instance, their meaning depends entirely on the context
and the intention or point of view of the person who utters them.
In short, there is no unified definition of any of them.
As for the unity of science movement, it was promoted by Carnap, whose
hero was Ernst Mach, who tried to put shackles on science. Einstein
called Mach a good experimental physicist but a miserable philosopher.
Among other things, Mach was directly or indirectly responsible for
Boltzmann's suicide in 1905.
Fortunately, Einstein rescued physics by deliberately violating
all of Mach's restrictions. But psychologists didn't have anyone
of Einstein's stature to protect them. For over half a century,
psychology in the US was strangled by behaviorism. In the 1960s,
cognitive science resumed the same issues as William James (1890).
For linguistics, Leonard Bloomfield (1914) wrote _An Introduction
to Language_, which related semantics to psychological issues. But
the behaviorists convinced him to ditch semantics in his 1933 book.
That was the mindset that led Chomsky to his emphasis on syntax.
These examples show how a premature "standard" based on a poorly
thought out "unification" can stifle progress. It violated
Peirce's first rule of reason: "Do not block the way of inquiry."
For more about these issues, see the article "Signs, Processes,
and Language Games": http://www.jfsowa.com/pubs/signproc.pdf
And by the way, I took the word 'nobler' in the subject line from
Shakespeare, but I was also thinking of the Buddhist notion of
Noble Wisdom, which attains a unity that transcends concepts.
The excerpt below is from the final chapter of my CS book.
In any case, I would encourage anybody who finds promising ideas
to pursue -- such as your dissertation -- to explore them further.
But before adopting them as a foundation for ontology, I'd need
more evidence that they could or would serve as a foundation.
See below, for example. I think that the Buddhist Noble Wisdom
is very promising. But I would not propose it as an ISO standard.
John
______________________________________________________________________
From the first paragraph of http://www.jfsowa.com/pubs/cs7.htm :
No theory is fully understood until its limitations are recognized.
To avoid the presumption that conceptual mechanisms completely define
the human mind, this chapter surveys aspects of the mind that lie beyond
(or perhaps beneath) conceptual graphs. These are the continuous aspects
of the world that cannot be adequately expressed in discrete concepts
and conceptual relations...
From the end of Section 7.3:
Discrete concepts divide the world into discrete things. The
arbitrariness of this division is a common theme of Oriental
philosophers. Lao Tzu said, “The Nameless is the origin of heaven
and earth, the Named is the mother of all things.” The world flows
according to the unnamed Tao, but the differentiation of the world
into discrete objects is a consequence of the discreteness of the
conceptual mechanisms and the words that reflect them.
By meditation on paradoxical sayings or koans, Zen Buddhism seeks to
undermine a person’s conceptual system and promote a direct experience
of conceptual relativity. The process cuts through many years of
cherished beliefs and automatic ways of thinking and acting. It requires
a painful letting go of familiar habits. But the result is a blissful
state of Enlightenment where the anxieties based on the old system of
concepts melt into insignificance. The most detailed statement of the
Buddhist theory of knowledge comes from the Lankavatara Sutra (Goddard
1938):
* Appearance knowledge gives names to things. It “belongs to the word
mongers who revel in discriminations, assertions, and negations.”
* Relative knowledge does more than classifying. “It rises from the
mind’s ability to arrange, combine, and analyze these relations by its
powers of discursive logic and imagination, by reason of which it is
able to peer into the meanings and significance of things.”
* Perfect knowledge “is the pathway and the entrance into the exalted
state of self-realization of Noble Wisdom.” Perfect knowledge does not
rule out the use of words and concepts, but it goes beyond them to a
state of nonattachment to any particular conceptual system.
Concepts are useful fictions that are not absolute. There is a Buddhist
saying that words are like a finger pointing to the moon: one who
focuses only on the words and the concepts they symbolize will miss the
reality they express, just as one who looks only at the finger will not
see the moon it points to. Nonattachment to any system does not mean
ignorance of all systems; appearance knowledge and relative knowledge
are important for everyday life. The enlightened one is free to use
concepts, but is not bound to them as absolute. Yet the path to
enlightenment requires a painful abandonment of the comfortable old ways
of thinking before any assurance is offered that the new way is better.
Ravi Sharma
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Marcel Fröhlich
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Gary Berg-Cross
Ravi Sharma
- Hence is it that unification of models of this physical universe are somewhat dependent on the unified processes of understanding in life sciences as well??
- Actually understanding is only applicable to life sciences and entities like us, or / and that nature (integral of physical universe and life) already has the required knowledge for future (evolution and destruction)?
Marcel Fröhlich
- Actually understanding is only applicable to life sciences and entities like us, or / and that nature (integral of physical universe and life) already has the required knowledge for future (evolution and destruction)?
Styrman, Avril E R
John, your story needs revision. You are basically restating the standard misinterpretation of Mach and embracing relativistic physics.
JS:
I would never try to prevent or avoid unification.
As for the unity of science movement, it was promoted by Carnap, whose hero was Ernst Mach, who tried to put shackles on science.
Once again, the unity of science movement has been going on ever since Thales, continuing through Aristotle, and it was in the center of Mach’s thought. It is notable that about all the greatest thinkers in history have expressed economy. Note 'simplest elements' in Aristotle:
When the objects of an inquiry, in any department, have principles, conditions, or elements, it is through acquaintance with these that knowledge, that is to say scientific knowledge, is attained. For we do not think that we know a thing until we are acquainted with its primary conditions or first principles, and have carried our analysis as far as its simplest elements. Plainly therefore in the science of Nature, as in other branches of study, our first task will be to try to determine what relates to its principles. Aristotle, Physics, bk. 1, ch. 1
Mach is not so different from Aristotle:
It is the object of science to replace, or save, experiences, by the reproduction and anticipation of facts in thought. . . . any stock of knowledge worthy of the name is unattainable except by the greatest mental economy. Science itself, therefore, may be regarded as a minimal problem, consisting of the completest possible presentment. The Science of Mechanics, pp. 481, 491
Carnap and the Vienna Circlers are guilty of a massive misinterpretation of Mach, which you are restating. While the logical positivists over-propagated economy into total rejection of metaphysics, Mach aimed at eradicating unnecessary metaphysics that is not needed and is thereby on the way of unified science and stalls optimal progress of science. In Mach’s terminology, ‘metaphysics’ means what we understand as ‘unnecessary metaphysics’, so don’t let that mislead you into thinking that he wanted to eradicate all metaphysics. The view the Mach rejected all metaphysics is incoherent with the fact that Mach himself suggested metaphysical principles in the center of unified science, i.e., principles by which science could be unified.
His central idea was that the Universe is a total gravitational system, where the principle that links inertia of mass to the total mass in space has become to be called Mach’s principle, and his other central ideas are neatly unified around this. When a mass object moves, its movement is relative to and affected by the rest of the mass in space, i.e., there is no such thing as ‘absolutely free movement’ that would not be affected by the rest of the mass in space. Therefore, Newton’s absolute space and time are not needed. The conservation law of energy makes sense when it is supposed that everything is interrelated. All these principles are implemented in Suntola’s unified physics.
JS:
Einstein called Mach a good experimental physicist but a miserable philosopher. Among other things, Mach was directly or indirectly responsible for Boltzmann's suicide in 1905.
Mach and Boltzmann knew each other very well. Mach even wrote Boltzmann’s obituary. Boltzmann was known to be mentally ill. It is quite drastic to accuse Mach of his suicide. Mach presented the hypothesis that there are no atoms, but his primary goal in the anti-atomistic hypothesis was to reach a non-mechanistic description of the atomic scale, i.e., to not to explain phenomena in that scale solely in terms of mechanistic movement of particles, which is by the way the contemporary dogma. Remember that gravitons have not been verified to exist.
JS:
Fortunately, Einstein rescued physics by deliberately violating all of Mach's restrictions.
You are conveying the myth of a genius who somehow fixed it all. Mach presented overall principles by which physics could be unified. His central principles are rejected in relativistic physics: Mach’s principle is rejected; the conservation law makes no sense there; absolute time is rejected in relativistic physics, but not in the way Mach intended, as Mach rejected relativistic physics (see excerpt below). As a result of rejecting Mach’s suggestions, physics remains disunified, nature has been declared non-understandable, and physics is seen as the task of developing mathematics for each disunified and parametrised branch, with no sight of the big picture. Einstein’s contributions are best seen as the initiation of the building of a parameter structure on the top of Newtonian physics, for parameters were needed to explain new phenomena in the context of otherwise Newtonian physics (where force is the starting point). It is notable that the stack of metaphysical parameters has been growing ever since: whenever a new phenomenon is encountered, a new parameter is invented to explain it. If parameter-invention can be called rescuing physics, then I guess anything goes. Do you think that is a good way to go, even it we have an alternative that explains everything at least as well, gives at least as accurate predictions, and without the parameters?
Avril
Mach. The Principles of Physical Optics — An Historical and Philosophical Treatment:
I am compelled, in what may be my last opportunity, to cancel my contemplation of the relativity theory.
I gather from the publications which have reached me, and especially from my correspondence, that I am gradually becoming regarded as the forerunner of relativity. I am able even now to picture approximately what new expositions and interpretations many of the ideas expressed in my book on Mechanics will receive in the future from the point of view of relativity.
It was to be expected that philosophers and physicists should carry on a crusade against me, for, as I have repeatedly observed, I was merely an unprejudiced rambler, endowed with original ideas, in varied fields of knowledge. I must, however, as assuredly disclaim to be a forerunner of the relativists as I withhold from the atomistic belief of the present day.
The reason why, and the extent to which, I discredit the present-day relativity theory, which I find to be growing more and more dogmatical, together with the particular reasons which have led me to such a view—the considerations based on, the physiology of the senses, the theoretical ideas, and above all the conceptions resulting from my experiments—must remain to be treated in the sequel.
The ever-increasing amount of thought devoted to the study of relativity will not, indeed, be lost; it has already been both fruitful and of permanent value to mathematics. Will it, however, be able to maintain its position in the physical conception of the universe of some future period as the theory which has to find a place in a universe enlarged by a multitude of new ideas? Will it prove to be more than a transitory inspiration in the history of science?
Sent: Saturday, May 6, 2017 3:47 PM
To: ontolo...@googlegroups.com
Subject: Re: [ontolog-forum] Unity or diversity, that is the question. Which is nobler in the mind?
Chris Partridge
inline...On Wed, Apr 26, 2017 at 3:28 PM, Chris Partridge <partri...@gmail.com> wrote:inline again ...BTW there are different kinds of ontology projects, and we may just be talking about different kinds.On 26 April 2017 at 11:43, <rrov...@buffalo.edu> wrote:inline below again...On Tue, Apr 25, 2017 at 2:29 PM, Chris Partridge <partri...@gmail.com> wrote:inline a few comments ...and one general comment. Your identification of the various ontological options is good, and it seems to me (from an engineering point of view) that one should explore whether and how they work. I hope that is what you are recommending.On 25 April 2017 at 13:03, <rrov...@buffalo.edu> wrote:Input in-line below...On Tue, Apr 25, 2017 at 12:02 PM, Matthew West <dr.matt...@gmail.com> wrote:Dear Michael
I think you’ve got the wrong idea of what a Top Level Ontology is. I know Barry described a TLO as a set of traffic lights, but for this audience (I hope) that is a slightly simplistic take. A next level of explanation would be that whatever your domain ontology is, there is TLO inside, and the only real question is whether it is explicit or implicit. I would want to argue that whatever your top level ontology is, it is worth knowing what it is. So how do you find out what your top level ontology is? Well here are some questions to help you work (some of) it out presented as a series of choices.
That's a interesting way to put it. But I would not insist that there is a TLO inside or implicit, though. Why? Because the domain developers may in fact either not have conceptualized a more abstract level or any implicit or subconscious concepts are so flexible that they underdetermine any particular would-be top-level. The investigation into any implicit top-level is an exploration into great abstractness, and can lead into confusion. It can lead to domain ontology developers feeling forced to select or identify what any supposed implicit top-level their domain ontology has. Which they don't. They should also not feel they have to adopt a particular pre-existing conceptualization, category or distinction (e.g. the continuant vs. occurrent).CP> I am assuming that when you talk about domain ontology developers you mean domain experts rather than ontology experts - if I have misinterpreted, I apologise.CP> In my experience, there is a fundamental choice here for projects. Domain developers/ experts or ontologists first. And it is not that one is inherently right (for the kind of business system development I am interested in), it is just (for me) whether one ends up with a better product at a reasonable cost.By 'domain ontology developers' I mean either domain experts or ontology developers, but not necessarily ontology experts. The onto developers may be domain experts and may not.I believe having both domain experts (or non-ontologist ontology developers) and ontologists working together from the beginning is the best strategy.
All the more better if each has knowledge and skills of the other (I think courses/training should be compulsory to each).
CP> In our BORO work, we take the ontologists first approach as we find it gives good results - in our experience most domain experts are not able to articulate fully what they know (for the more technically minded see Ryle on anti-intellectualism - also some of my papers) - we find data-driven approaches supplemented by experts a better route - one not available for all domains, as they may not have the right kind of structured data resources.
Would you please clarify 'data-driven approaches'?CP> A typical example is a legacy modernisation project, where there is an existing operational system (SAP or Oracale Financials or ...). The task is to migrate the data to a new system or to a data warehouse or ...CP> My argument has been for a while (see e.g. my 1996 book) that people are not really up to the task of specifying things to the level of detail needed by computers, so existing operational data has at least the merit of being proved to work. And I'm suspicious of experts' expertise. Searle (somewhere, maybe social construction) has a few paragraphs where he makes the point that experts usually don't know in terms of being able to articulate, and sometimes evaluate, their knowledge - and as I said earlier there is the whole Ryle anti-intellectualism debate that has heated up recently. Not saying that experts aren't needed, just that they need to have the right kind of role.Certainly possible. I'm sure not all persons have the degree of metacognition to articulate and reflect in that way.
Do you have a link to that debate/paper and is your book available in pdf?
Tangent: also, determining 'expertise' is one of those difficult tasks, as some philosophy literature and military circles point out. I've seen the latter formally assert to use 'professional' rather than 'expert' because of the vagueness is expertise and I tend to agree.CP> I agree that typically asking domain experts to identify the implicit top level leads to confusion, so we don't ask them (as an aside, this is common practice for business/conceptual modelling practitioners, even for simple non-ontological business models).
I did not say/mean not to ask them because it might lead to confusion. No, that would be wrong because ontologists need domain experts, and domain knowledge, to create accurate ontologies. Domain experts serve the essential task of (a) providing knowledge, (b) verifying ontological characterizations and ontology content, and (c) quality control...at least ideally!CP> Depending upon what you mean, I'd certainly not ask them to do (b) - at least from an ontological stance.They should see the characterizations, if only from a domain stance, i.e., to make sure that the ontological characterizations reflect the domain knowledge (if in a watered down way). The onto characterizations should obviously not distort or mischaracterize and they are there in part to ensure that. THis is what i'm getting at.
It's possible that domain experts attempt to identify potential (but not necessarily actual) implicit top-level conceptualizations causes confusion, but not necessarily. What i meant was that because foundational ontological inquiry is so abstract with various concepts either concepts of art (jargon) or vague, the very inquiry itself can lead to confusion, particularly for people not versed in the respective concepts, in the formal analysis, and philosophical ontology. It's like formal logic: people need to be trained in it...FOL, for instance, does not come naturally. Likewise, I suspect, for formalizing top-level aspects. Hence, its easy to get into confusion. The concepts are so vague that a non-ontologist can easily (and rightly in many cases!) ask: "Why are you using that top-level category?", "Why do you define 'object', 'process', '...' that way and not another?", "Why do you say that continuants and occurrents are mutually exclusive?"CP> I'm suspicious of this argument or way of expressing things.CP> It seems to me that you are going about things the wrong way, if the domain experts don't understand the intellectual technology (ontology) why are they being asked to evaluate it? It just sounds as if the team roles have not been thought out.Not saying they don't understand it. Some will, some won't. They should evaluate the match between their domain knowledge and the ontological characterization, but not exclusively...as a team effort. Another way to express what I mean is this: the process needs both the ontologist and the domain expert. Input from the domain expert is essential regardless and because of them not being ontology specialists. The fresh perspectives, hopefully lack of bias toward this or that ontological distinction or category, and fresh eyes is important. We need the perspective of domain experts because the ontological characterization should not falsely represent their domain or in a way they do not agree with regardless of the level of generality/abstractness. The ontologist, whether through having a favorite ontological theory, philosopher, or otherwise, may have a particular bias for this or that way of categorizing or this or that distinction. To minimize that being imposed on domains, the domain experts can introduce a worthwhile critical eye.CP> By the way, the questions are good and need to be answered, just can't see how the domain experts are expected to be the final arbiters.I didn't say/mean they're expected to have final say. It should be a team effort.From an efficiency point of view, if possible, I'd try and do the foundational ontology evaluation before using to build a domain ontology.Evaluate it before using it with a domain ontology, agreed. The evaluation should be done by both ontologists and domain experts doing the evaluating.
But I don't agree that the foundational ontology should be used to build a domain ontology. Domain experts do not necessarily have a particular implicit foundational ontological conceptualization in mind vis-a-vis their domain knowledge. If they do, that can be explicitly formalized into a foundational ontology for that domain ontology. Domain knowledge is acquired and pursued independent of doing formal ontology. So from a more bottom-up approach, look at the domain, develop the onto, and if desired add an upper layer according to this or that criteria, conceptualization, implicit concepts, etc. But maybe I misunderstand what you mean by using the foundational onto to build a domain ontology.CP> However, I get the feeling you are suggesting that because the domain experts cannot be easily asked to make a choice, that this somehow means that this choice should not be made in the project. If you are suggesting this, I do not see the argument.No, I do not suggest that. I meant that it's not correct that necessarily there is an implicit top-level conceptualization in a domain ontology or in the mind of domain experts. And I meant that ontologists should not try to pull some implicit top-level conceptualization from the minds of the domain experts if there isn't one, nor should they try to coax, convince or impose their own preferred top-level conceptualziation on domain experts. For example, the continuant-occurrent distinction (of a certain interpretation/sense of each category) is something that is often espoused time and again, asserted as being the way the top-level should be, but with little justification or explanation of historical origins. The oft-held mutual exclusivity of the categories is something typically not demonstrated when these dicussions take place (but they should because that has been contested in the literature). Some have questioned the interpretaion and sense of the categories, e.g., the wholly present aspect and other properties of each. The exchange between domain experts and ontologists is of course worth making, but the former may simply not have an implicit top-level in mind, may not agree with the top-level distinctions the ontologist introduces, etc. Also, the danger is that given the specialist knowledge in ontology development, and given domain expert lack of interest in such abstract levels, domain experts may simply accept whatever the ontologist says. This is not correct because they would be blindly accepting the onto commitments, metaphysical assumptions, methodologies, etc. And the consequences of this are that domain expert concepts and objects might be mischaracterized, falsely defined or pidgeonholed into this or that philosophical or methodological theory.CP> It sounds as if you see an essential part of the goal of an ontology project is to get the domain experts to understand and accept the ontology - particularly the foundational aspects. I would not willingly join such a project.Two separate points.
First, I believe it is essential for them to understand the ontology. This will ensure the ontology reflects their domain as accurately as possible, but also helps ensure the ontology is not simply imposing a particular metaphysics, some of which might mischaracterize their domain (hence importance of them understanding the ontology).
Second, they do not have to accept the ontology, but if not then I'd think that would be some cause for changing it. (perhaps analogously to helping a customer with a service).
With that clarification, why would you not?CP> It also seems to me that you are not using the right tools to assess the ontology - I'm sure you get weird answers if you asked domain experts, particularly those with no understanding of ontology. Why is it essential to assess the ontology in this way?CP> Isn't there a whole tradition that recognises rational reconstruction (Carnap) / regimentation (Quine) changes the meaning of the previously unregimented structure. My guess would be that there is no implicit top-level ontology in the minds of the domain experts, and that introducing it would change the meaning often in ways they do not feel happy with. Isn't this part of the process?Right--they might have no implicit top-level conceptualization. Which is why if they desire an upper-level, then work with them to develop it that is consistent and accurately representative with their domain. The main theme here is not to mischaracterize or impose particular ontological conceptualization on domains.
CP> "... , asserted as being the way the top-level should be, but with little justification or explanation of historical origins." I would completely agree this is wrong - it needs to be explained. But I'n not sure the domain experts are the right audience for this.Not sure what you're saying here, but if you're saying the suggested top-level should be given justification and explanation then I agree. Perhaps a detailed expose to domain experts is much, but again, they should understand any ontology their ontology is being subsumed under and the way their domain is being ontologically characterized.
Again, the fact is that the generality is so high that there may not be an implicit top-level in the minds of the developers. If there is one it may be of a vague, undetermined and underspecified nature. Afterall, non-philosophers, non-specialists in this area, do not usually (let alone instinctively) consider persistence and other formal ontological aspects. It's an exercise in part in psychology vis-a-vis concepts. Studies may suggest fundamental concepts, e.g. living vs. non-living. But these do not necessarily change over time to become a full-fledged implicit top-level conceptualization in the minds of developers underlying their explicitly specified domain ontology.
This is not to say that no one has implicit top-level ideas in mind, nor is it to say that they might not want to use some particular top-level conceptualization.It is one thing to enjoy, as I do, explicitly specifying and formalize the most general (top-level) aspects in an attempt to understand not only concepts but the world.
But it is quite another to suggest a domain developer definitely has an implicit TLO or must have one, or must select from a set of pre-existing distinctions (e.g. 1-3 below). Pre-existing distinctions may not be sufficient, may not be what they think of.1. Do you think that physical objects pass through time, or do you think they are extended in time (as well as space)?
2. Do you think classes/types (e.g. bicycle) always have the same members, or do you think membership can change over time?
3. Do you think that an activity can also be a physical object, or do you think that activities and physical objects are quite separate things?
#1 reflects an ordinary philosophical distinction about persistence in time. The problem is that that distinction has many variations, open questions, etc.#3 assumes a distinction between activity and physical object, reflecting that distinction.The concepts of object and activity are themselves open to variation given their inherent generality.What you can’t do is say “both” because that will lead immediately to a contradiction (nor can say “neither”).
Not necessarily. It's often asserted or assumed, but not necessarily. The philosophical literature includes theories about all these things.
But in any case, it would be helpful for this forum to show how any contradiction would arise...The choices you make (and these are just a sample) are your ontological commitments, and a Top Level Ontology is principally a particular set of these ontological commitments. BFO exemplifies such a set of ontological commitments, a different set is exemplified by ISO 15926-2 (or my book “Developing High Quality Data Models”).
The value then of the TLO is that you can check your domain ontology against it to make sure it conforms to your chosen ontological commitments. This is where the traffic lights come in.
Yes, but the domain developers need not chose a top-level set of ontological commitments, nor a tlo.The keyword is 'chosen'. But some tlo users I've spoken with express they do not have a choice. Rather, they simply are told (e.g. via employer) to use this or that tlo because of some userbase. Some have expressed they do not agree with the given tlo (e.g. bfo). If a user gets onboard with a tlo simply because of a userbase, then it's not choice for ontological commitments or even utility, but of popularity and perception (not necessarily good or true) of utility or benefit.It turns out that if you just toss a coin to make your choices on these questions, most of the combinations are not coherent, but there are two combinations (with variations) that are reasonably coherent (though proponents of each will argue that the other is not really). These I will characterise as 3D and 4D:
3D (e.g. BFO)
1. Physical objects pass through time and are wholly present at each point in time.
The concept of 'wholly present' has been contested in the phi. literature.2. Classes/types can change members over time (For the type car, the number of cars is different today and yesterday).
This is based on the same distinction but theories have been put forward about objects being more like activities than the distinction would have. See the Waterfall paper by Galton and Mizoguchi; Stout; and others.There are activity-like aspects of objects and vice versa. The priority of objects over activities need not be help as dogma. Hence, theories like 4D, Whitehead, and others. But similarly, the 4D need not hold priority either. Hybrid views and novel ones are possible.
4D (e.g. ISO 15926)
1. Physical objects are extended in time as well as space.
2. Classes are defined by their membership (they are sets). So, the type car is the set of cars over all time, cars yesterday is a subset of this.
3. Physical objects and activities can overlap, so a person is their life, not separate from it.
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