Paul, (01)
The distinction between semantic networks and ontologies implies a more
general difference between knowledge representation technologies and
languages (as FOL, semantics nets, frames, rules, DL, SW languages) and
foundation Ontology as the general science of entities and relationships. (02)
In computer science, artificial intelligence, and software engineering, the
science of reality [studying how to represent and reason about the world,
both external and conceptual] is commonly (or confusedly) regarded as an
extension or an external layer of logical calculi and formal languages. As a
consequence, a real world ontology is reduced to a sort of formal logical
ontology, which is specified as consisting of the following logical
elements: concepts (classes, objects, or categories) with their
characteristics (attributes, slots, functions, roles, or properties) and
relations (generalization and specialization, functions) restrained by
logical axioms (assertions) and exemplified by instances of classes and
specific properties. (03)
Without the reality check restraints, our intutive, individual ontologies
may be as various as: 'an explicit specification of conceptualization', 'a
theory of content', 'a theory (a system) of concepts/vocabulary used as
building blocks of information processing systems', 'a set of agreements
about a set of concepts', or 'the representation of the semantics of terms
and their relationships'. Or, 'the class hierarchy in object-oriented
paradigm', 'a complete schema of the domain concepts', 'an
entity-relationship schema with subsumption relations between concepts'. You
may risk meeting also such definitions as 'conceptual patterns', 'concept
heterarchies or hierarchies', 'a body of conceptualizations', 'schemata', or
'metadata scheme', 'a common set of terms', 'a controlled vocabulary of
terms', 'a representation vocabulary', or 'a body of knowledge'. (04)
Such a transient state of affairs may be partly justified by the
long-standing disagreements over the scope and nature of the subject matter
even among its greatest scholars. For, when taken as pure and abstract
knowledge, Ontology is formulated as different as: the science (account) of
entity (or being) in general; the knowledge of the most general structures
of reality; the theory of the kinds and structures of things in every domain
of reality; the study of entity types and relations; the most general theory
concerning reality, being, or existence; a collection of absolute
assumptions; the study of change; the science of all possible worlds and
everything conceivable; the study of semantic values of natural and formal
languages and ontological commitments about the world. (05)
This inherent ambiguity causes the researcher to decide whether the whole
activity is about the inquiry of entity, its forms and properties, or just
about some general concepts with their formal logical relations. Or, are we
supposed to deal with 'the nominal' ontology of terms and their semantic
relationships instead of 'the world' ontology of entity types and their
external relationships? Because of this manifold interpretations, one has to
decide on the research line: either the world ontology (realistic and
veridical), or the concept ontology (conceptual and notional), or the word
(terminological) ontology (linguistic and nominal). (06)
In fact, there is a unified foundation ontology (UFO) dealing with the
world, its things, beings, and relationships, and a plurality of domain
ontologies dealing with the specific regions, parts, domains, or realms of
reality. (07)
Accordingly, computing ontology is all about the representation of the
world, its entity states, changes, and relationships, in machine-processed
forms. In other words, there is Ontology taken in the primary sense and
ontologies in the secondary senses. Its basic meaning consists in being an
account of reality and realities and their associative orderings. Thus,
Ontology is primarily concerned with the types of entities and relationships
in the world. Secondly, it studies how things in the real world relate to
concepts and associations in the mind, to coded representations and
structures in machines, and to words and sentences in natural languages. (08)
At the end, i'd like to refer all of us to a seminal work of Randall Davis &
co-authors, What is a Knowledge Representation? AI Magazine, 1993, which is
generally in line with the positive view, except maybe one traditional for
logicians consfusion that ''the "world" we are interested in capturing is
the world inside the mind of some intelligent human observer (e.g., a
physician, engineer, etc.)''. Here are some characteristic selections: (09)
''a KR is a set of ontological commitments'', the intutive assumptions about
<how to view and reason about the world>; (010)
''Ontologies can of course be written down in a wide variety of languages
and notations (e.g., logic, LISP, etc.); the essential information is not
the form of that language but the content, i.e., the set of concepts offered
as a way of thinking about the world. Simply put, the important part is
notions like connections and components, not whether we choose to write them
as predicates or LISP constructs.''; (011)
''... all the representation technologies...supply only a first order guess
about how to see the world: they offer a way of seeing but don't indicate
how to instantiate that view. As frames suggest prototypes and taxonomies
but do not tell us which things to select as prototypes, rules suggest
thinking in terms of plausible inferences, but don't tell us which plausible
inferences to attend to. Similarly logic tells us to view the world in terms
of individuals and relations, but does not specify which individuals and
relations to use''. (012)
Kind regards, (013)
Azamat Abdoullaev (014)
EIS Encyclopedic Intelligent Systems LTD (015)
. (016)
----- Original Message ----- (017)
From: "Paul Prueitt" <psp@xxxxxxxxxxxxxxx>
To: <protege-discussion@xxxxxxxxxxxxxxxx>
Cc: "Brand Niemann" <bniemann@xxxxxxx>; "Alan Ruttenberg"
<alanruttenberg@xxxxxxxxx>; "Andrea Proli" <aprol@xxxxxx>; "Azamat"
<abdoul@xxxxxxxxxxxxxx>; "John F. Sowa" <sowa@xxxxxxxxxxx>; "Paul J. Werbos"
<pwerbos@xxxxxxx>; "Susan Turnbull" <susan.turnbull@xxxxxxx>; "Tim
Berners-Lee" <timbl@xxxxxx>
Sent: Friday, March 17, 2006 12:29 AM
Subject: RE: [protege-discussion] Re: semantic networks and ontologies (018)
>
> I posted Bert's note at:
>
> http://www.secondschool.net/beads/ontologyMapping/29.htm
>
> There are related posting (from other forums at [28], [27] etc... links
> from
> this post)
>
>
> Paulo,
>
> These are important questions that will become more transparent as the
> research community completes work on description logics....
>
> In Nardi and Brachman's first chapter in the landmark "DL Handbook"
>
> we find enlightenment on several points
>
> 1) the history of the discipline that has created the current variety of
> description logics
> 2) a clear understanding of what DL is and how it functions
>
> but we also find, I claim, a deficiency in the why questions, as reflected
> in the nature of purpose.
>
> Chapter one is at
>
> http://www.inf.unibz.it/~franconi/dl/course/dlhb/dlhb-01.pdf
>
>
> Perhaps we can undertake a type of global peer review? Let us look at
> the
> issues at the deepest level?
>
>
> What is(are) the purpose(s) of description logics? If the purpose is to
>
> define computational systems that "find implicit consequences of its
> explicitly represented knowledge" (pg 6)
>
> then this is what is achieved (I claim). Yea for the good guys !!
>
>
>
> But does this purpose fulfill all aspects of our social need to have
> "intelligence" behind web services and information structures (encoded in
> OWL, for example)?
>
> Quote from Section 1.1
>
> "Research in the field of knowledge representation and reasoning is
> usually
> focused on methods for providing high-level description of the world
> that
> can be effectively used to build intelligent applications." (page
> 5)
>
>
> Is the "implicit" asserted meaning to the term "intelligence" the sameAs
> the
> meaning of "intelligence" in the cognitive neuroscience discipline, or the
> cultural anthropology discipline, or the behavioral science discipline, or
> (what about) the everyday sense that common people have regarding "their"
> intelligence"?
>
> I claim that this assertion made by Nardi and Brachman is controversial,
> and
> yet it is asserted as if a truth that cannot and should not be questioned?
> Am I right about this assertion? Do they wish the reader to not question
> their assertion?
>
>
> Is there anywhere something that should be called an "intelligence
> computer
> program"? Can someone just point this out by name and perhaps by some
> URI?
> Then we can make an interdisciplinary review as to whether or not this
> assertion by Nardi and Brachman is justified?
>
> Or does Nardi and Brachman not agree that the implicit assertion is being
> made? Do program managers at NSF, DARPA and NIST pretend that this
> assertion is justified? What is the reality here?
>
>
>
> Does "intelligence" come from the finding of implicit consequences? As
> you
> point out, what if a specific OWL ontology is really not inline with the
> reality that is modeled. We can take as an example, the BioPAX vocabulary
> (ontology).
>
> I claim that BioPAX (www.biopax.org) is the best example of a good
> bioinformatics ontology. To what extent is BioPAX a perfect model of
> cell
> and gene expression?
>
> Suppose we compare
>
> 1) Hilbert mathematic's relationship to Newtonian mechanics
>
> to
>
> 2) the BioPAX ontology's relationship to cellular and gene science
>
> If Hilbert mathematics is given a 9 on a scale of 1 - 10, what would a
> (non-computer scientist) biologist give to BioPAX?
>
> I conjecture that if I ask Gerald Edelman his answer will be "2" or
> perhaps
> "1" (I conjecture), but that is because that are processes important to
> him
> that seems not expressed in the BioPAX vocabulary.
>
> To go along with my comparison, we remind the reader that a judgment is
> being made that BioPAX has implemented, as well as possible, the standards
> related to RDF and the various description logics.
>
> Intelligence has been used in the development of the OWL standards as well
> as in the specification of the BioPAX vocabulary and assertions (the
> BioPAX
> "axioms" as John Sowa would say). But is a perfectly designed structural
> index on implicit and explicit assertions in the BioPAX vocabulary an
> intelligence computer program?
>
> How do others feel about this?
>
> We can honor what workers in the DL field have done and are doing; but we
> as
> a society need to get our IT corrected. Yes?
>
>
> Walks Forward
> Taos New Mexico
>
>
>
>
>
> -----Original Message-----
> From: protege-discussion-bounce@xxxxxxxxxxxxxxxx
> [mailto:protege-discussion-bounce@xxxxxxxxxxxxxxxx]On Behalf Of Paulo
> Gottgtroy
> Sent: Thursday, March 16, 2006 12:57 PM
> To: protege-discussion@xxxxxxxxxxxxxxxx
> Subject: [protege-discussion] Re: semantic networks and ontologies
>
>
> Hi,
>
>
> Just to add some points/questions:
>
> - Hermaphrodite: make it father and mother of.
>
> What about something being true in a context? What about evolving this
> truth
> to an "almost true"? How many operators we will need to represent temporal
> constraint, uncertainty, etc? What about flexibility instead of formalism?
> I
> do beleive that there is no "truth" when you are representing knowledge
> since this is itself is a conceptualization. Formalism brings good things
> but don't forget the bad things.
>
> Maybe, the most important question is How do I build good models? DL is a
> powerful language but if you don't know how to build a good model you
> will,
> proably, messing up and inferering wrong knowledge also. We have been
> mastering our representation languages capabilities but our modelling
> skills
> are still our big weakness. No matter wich formalism, a good model will be
> always better in a "weak" language than a poor model in a powerful
> language.
>
> Ontology is a similar ambiguous word - that is really "true". As Sowa
> argues *i**f the world had a unique decomposition into discrete objects
> and
> relations, the world itself would be a universal model, of which all
> accurate models would be subsets.* Do we know any unambiguous world ?
>
> Paulo
>
>
>
>
> On 3/17/06, bvn@xxxxxxxxxxxxxxxxxxxxx <bvn@xxxxxxxxxxxxxxxxxxxxx> wrote:
>>
>>
>> Hello,
>>
>> as pointed out by Paul, the names are used with many different meanings.
>> Semantical networks historically are a graphical language in which a node
>> represents a concept and an arrow (link) represents a relationship
>> between the connected concepts.
>> They have been given semantics but it has been proven (Woods 1975) that
>> the given semantics were ambiguous. Different people interpreted the
>> links differently, hence semantical networks defined at the end of the
>> seventies were not usable for formal and clear knowledge representation.
>>
>> From these concerns research went on and the representation logics have
>> been refined and given more formal ground. One of the siblings are
>> description logics, others are answer set programming and first order
>> logic with inductive definitions (the latter have more their roots in
>> logic programming).
>>
>> As graphical language a semantical network is very useful, but you have
>> to give it a good formal account in order to do correct inference. This
>> you can do by interpreting your graph as your preferred logic. But be
>> aware, another may have chosen another interpretation hence you have to
>> mention it.
>>
>> Ontology is a similar ambiguous word. The least interpretation is that it
>> is a vocabulary of concepts, functions and relations for a given problem
>> domain that you can use to represent particular information in that
>> domain.
>> E.g. {father_of, mother_of, man, female, child_of} can be an ontology for
>> representing human's families.
>> Typically such a vocabulary induces (not mentioned) formal relationships:
>> e.g. Someboby who is a 'father_of' is a man.
>> These implicite and natural relationships are often considered part of
>> the ontology.
>> Furthermore as for semantical networks, you have to state your 'logical
>> context'.
>> E.g. stating that you use an OWL-full DL ontology for a family domain
>> precisely defines the boundaries of formal mathematics and the use (the
>> problem domain).
>> Leaving out OWL, full DL and your problem domain, may cause difficulties
>> for other to interprete the truthness of your information.
>>
>> Eg. You probably assumed that on my proposed family domain the integrity
>> contraint holds that somebody who is a father_of someone canNOT be a
>> mother_of the same person. But what do you do with an hermaphrodite?
>>
>>
>> Bert
>>
>>
>>
>>
>> On 3/16/2006, "Marko Rodriguez" <marko@xxxxxxxx> wrote:
>>
>> >
>> >I think that the difference between ontology and semantic networks is
>> >this:
>> >
>> >An ontology defines the type of entities and relations that can be
>> >instantiated in a semantic network... It just so happens that an
>> >ontology can also be represented by a semantic network. *loopy dizzy*
>> >
>> >Marko.
>> >
>> >
>> >
>> >On Wed, 2006-03-15 at 09:52 -0700, Paul Prueitt wrote:
>> >> The primary problem is in how terms are used, by different
>> communities. The
>> >> IT community took a term "ontology" and gave it a new process of
>> definition.
>> >> This process has been a research question, up to now; without clarity
>> on
>> >> what "is" computational ontology.
>> >>
>> >> An adjustment of terms seems almost impossible, and thus the confusion
>> will
>> >> continue.
>> >>
>> >> -----Original Message-----
>> >> From: protege-discussion-bounce@xxxxxxxxxxxxxxxx
>> >> [mailto:protege-discussion-bounce@xxxxxxxxxxxxxxxx]On Behalf Of
>> >> Yolanda
>> >> Blanco Fernández
>> >> Sent: Wednesday, March 15, 2006 7:56 AM
>> >> To: protege-owl@xxxxxxxxxxxxxxxx; protege-help@xxxxxxxxxxxxxxxx;
>> >> protege-discussion@xxxxxxxxxxxxxxxx
>> >> Subject: [protege-discussion] semantic networks and ontologies
>> >>
>> >>
>> >>
>> >> Hi,
>> >>
>> >> which is the difference between a semantic network and an ontology?
>> >> Thanks!
>> >>
>> >> Kind regards,
>> >>
>> >> Yolanda
>> >>
>> -------------------------------------------------------------------------
>> >> To unsubscribe go to
>> http://protege.stanford.edu/community/subscribe.html
>> >>
>> >>
>> >>
>> >>
>> -------------------------------------------------------------------------
>> >> To unsubscribe go to
>> http://protege.stanford.edu/community/subscribe.html
>> >>
>> >--
>> >Marko A. Rodriguez
>> >CCS-3 Modeling, Algorithms and Informatics
>> >Los Alamos National Laboratory
>> >Phone +1 505 606 1691
>> >Fax +1 505 665 6452
>> >http://www.soe.ucsc.edu/~okram
>> >
>> >-------------------------------------------------------------------------
>> >To unsubscribe go to
>> >http://protege.stanford.edu/community/subscribe.html
>> >
>> -------------------------------------------------------------------------
>> To unsubscribe go to http://protege.stanford.edu/community/subscribe.html
>>
>>
>
> -------------------------------------------------------------------------
> To unsubscribe go to http://protege.stanford.edu/community/subscribe.html
>
>
> (019)
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