1.  Ontology

2.  Existence 

3.  Knowledge, Cognitive Knowledge & Ontology 

4.  Meta-Ontological Perspective - Some  Principles 

5.  Ontology Building Methodology

6.  Conclusive remarks


 References

 In the Top-down Object-based Goal-oriented Approach  (TOGA meta-theory, 1993), ontology  is a relative concept, its meaning depends on: 

- intelligent agent's (IA) perception and comprehension properties (capacities) 
- intelligent agent's IPK, what includes: 
    -- limits related to the possibility to access to the information 
    -- goal-oriented constrains, i.e. what does not serve for a selected class of problems "does not 
       exist". 

For example, for a robot which distinguishes only white and black colors, only these two colors exist. Therefore its ontology does not include such concepts as red , blue , ...
The old "pandemic" conflict in philosophy between ontology and epistemology is now an acute disease  in computer science, artificial intelligence and emerging computational  philosophy.
As we see, a key meta-problem, in order to understand/comprehend ontology, is a comprehention and a human consensus related to the notion of existence.

The above TOGA idea has been modified and expressed by J.Sowa*, as follows:

"The subject of ontology is the study of the categories of things that exist or may exist in some domain. The product of such a study, called an ontology, is a catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D. The types in the ontology represent the predicates, word senses, or concept and relation types of the language L when used to discuss topics in the domain D. "

The main difference between these two definitions relates to the fact that Sowa, according to Minsky**,  assumes a language-based semantic network as an initial platform for the conceptualization of ontology, when in TOGA,  the fundamental conceptualization platform is not a language but an abstract objects network (abstract objects graph with relations and changes), included in TAO ( Theory of Abstract Objects)***. This last perspective generalizes  sources of information, is language independent,  every semantic network is a network of abstract objects, and also enables to conceptualize images, other products of  IA senses and "imagination" .

Meta-remark

It is interesting to remark that semantic-network is graphically represented by an abstract-object network, but in order to describe an abstract object network we use a semantic network. In other words,  in meta-ontology we may use, either semantic or abstract object network. Anyway, this choice is not the ontological but epistemological problem.

-----------------------

(*) [ http://www.jfsowa.com/ontology/index.htm, visited 14 Mar.2007, for more: John F. Sowa, Knowledge Representation: Logical, Philosophical, and Computational Foundations, Brooks Cole Publishing Co., Pacific Grove, CA, ©2000. Actual publication date, 16 August 1999]

(**) Marvin Minsky.  Semantic Information Processing, MIT Press, 1968.

(***) TAO is a sub-theory of TOGA

Everything which enables IA to change a pre-selected domain-of-activity and is representable in the concepts of TAO (Theory of Abstract Objects, which is a component of TOGA), can be considered as existing.

In general, it is rather difficult to obtain consensus on the extrapolation of the concept  existence over and outside of the human perception of the human life and the physical world.

Here, we may  accept a relative, domain-dependent notion of  'existence'.

For example,  in an abstract domain defined as the set of real numbers, the number  2.34658921897 exists.

 Remarks

1) Ontology of an intelligent entity (=IA ) can be changed only either by itself or by changes of its perception system. 

2) The concept 'ontology' is closely related to the concept 'epistemology' 
     - In philosophy, epistemology is the general theory of cognition focused on the questions: 

 

How humans recognize mentally what "really" exists?   What are limits of  such our  recognition/cognition?

3) From the philosophical point of view, where absolute solutions and explanations are searched, we can 
consider the concept  'absolute ontology'. 
Absolute ontology could either be build as an extrapolation and synthesis of all available applicable ontologies, or obtained by an internal "mental discovery" of an intelligent subject. 
In the first case, to select "all available applicable ontologies" is practically impossible. 
In the second case, "mental discovery"  can be interpreted in many different manners....

4) Absolute meaning of existence
With the concept of absolute ontology are closely connected studies of existence based on the assumption of its absolute, metaphysical, not cognitive meaning., see for example Stanford Encyclopedia of Philosophy.
Such paradigms are not  congruent with  goal-oriented cognitive assumptions of  TOGA where the concept 
of absolute, as absolute true, is considered as useful only in the different types of manipulation of ignorance, or as an operative "assymptotic" but not existing (in our domain of activity) entity, for instance, like as  bundaries of an open interval in mathematics.

Remarks:
Questions related to "absolute meaning of existence" and to "absolute ontology" seem to be close to, so called, "ill formed questions".

Most frequent, in the subject matter literature, notion of knowledge is : 
'facts, experiences,  and different theoretical and technical resources which when used
enable humans to act efficiently'.

In this sense, to know something refers, in natural languages, to the capacity of  the application of either information or knowledge, or preferences, all together. 

In  TOGA, 
 

From the cognitive perspective  knowledge and preferences consist segments of reasoning chains of IA  related to the domain D, for example:

    Knowledge1 --> Knowledge2--> Preferences1 --> Goal --> Knowledge3 -->  ... --> KnowledgeN.

 From such perspective in TOGA there are distinguished descriptive knowledge and operational knowledge.

 The first are expressed as : relation rules, physical laws, theories, models.

 The second are expressed as : algorithms, methods, instruction, procedures, they  specifications and  cause IA's 

 actions.

Meta-remarks on definition-making: Let us mention, in TOGA, the concept definition, in order to have a sense, has to be goal-oriented (in explicite or implicit manner). 
Therefore, the goal/purpose of a definition is its key generic aspect. In consequence, 
 

From the linguistic perspective, a cognitive knowledge is a knowledge constructed and applied in cognitive recognition and reasoning processes.
From the perspective of the meta-ontology development, a clear formal relations betwee such concepts as information , knowledge and ontology are essential. They are closely related to their internal structures (and/or representation), see for example "knowledge structure". 
In general, the concept "definition-making" requires a separate treatment in an integrated context of computational philosophy, i.e. including human and computer science: ontology, epistemology and  prakseology.
-  Theoretical fundations of computational definition-making are essential in TOGA. 

Links:
- Some interesting but not TOGA-based contributions to the ontology study: Onto-Med (some publications)
   Laboratory of Applied Ontology,    Ontology-Driven Conceptual Modelling.

- UNESCO - ENCYCLOPEDIA OF LIFE SUPPORT SYSTEMS (EOLSS) - RESEARCH PROJECT:

   Knowledge Management, Organizational Intelligence and Learning, and Complexity
- Software engineering perspective (according to Stanford's Knowledge System's Lab):  Sites Relevant to Ontologies

   and Knowledge Sharing . 

    Remarks: 
      In my opinion , acceptation of the Tom Gruber's definition of ontology " An ontology is a specification of a

      conceptualization." requires a serious effort  for the formulation of an acceptable computational definition of a

     specification  of a conceptualization.

- According to the TOGA meta-theory, for every mental process of an intelligent observer of  intelligent entities, ontology is not separable part of the triple: 

- Therefore all of them are either explicitly or implicitly goal-oriented (teleological). 

- On the other hand, this process is impossible without formally distinguished his/her/its: information, preferencesand knowledge structures/bases. (See references below)

This domain is recently strongly investigated in software engineering according to its particular needs and technologies, see for example: "...IFOMIS’s Basic Formal Ontology (BFO) is a philosophically inspired top-level ontology (Grenon and Smith, forthcoming) successive phases, or temporal parts. Entities that occur are processes or events ..." [Ontological Theory for Ontological Engineering: Biomedical Systems Information Integration James M. Fielding, Jonathan Simon, Werner Ceusters , Barry Smith, Proceedings of the Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004), Whistler, BC, 2-5 June 2004]. The recent product in this field is "Protègè" (2005),  http://protege.stanford.edu/.

- From the systemic, more general than software engineers perspective, meta-ontology refers  to the  most universal domain-independent concepts used by humans but which have their concrete representations (in frame of top classes of observables: objects, relations, changes - according to TOGA) in, so called, the real world.
For example: 
     system -->a representation, D --> factory, 
     action -->a representation, D --> swimming.
where:
     X--> a representation, D--> Y    denotes "Y has attributes of X in a domain D".
     In abstract domains   "Y is a  sub-class of  X".

Meta-ontology is based on the extrapolation of  common properties of  local ontologies to an abstract cognitive/ mental space.
Meta-ontology is  based on the consensus related to the arbitrary chosen system/interrelations of axiomatic concepts and rules. Usually they are expressed in the languages of mathematical theories, such as, set theory, functional analysis, graph theory, and so on.
From the socio-cognitive TOGA perspective meta-ontology is not any general/absolute ontology in the sense of "what really exists" but tends to the generalization of individual ontologies of intelligent beings. It means  it can be seen as a component of the common conceptualization framework enabling reciprocal comprehension and common actions of human like reasoning entities ...

5. Ontology Building Methodology (OBM)

In TOGA, methodology of an ontology building follows exactly the TOGA third  component, i.e.  Methodological RUles System (MRUS) .

TOGA is a proposal of a systemic computational top-down goal-oriented knowledge ordering. Therefore it requires not only an accurate top-down choice of concepts but also an explicitly accepted heuristic definition-making rules.

TOGA Definition-Making starts from  most general concepts with a maximal systemic denotation domain and with a minimal set of necessary attributes used in definients. It means, the concepts selected and defined at the begining have to be before used in the specification of the initial goal of the intended work.

The terms used in definition should be either axiomatic or should be concepts from another formal theory, or have to be just included in this ontology.

.The top-down specialization and decomposition of the goal require  specialization and modifications of definitions. Therefore

    OBM has to be an continuous  incremental and iterative task during every complex project.

The same domain abstract or real object can be seen from different perspectives , distance and using different tools.  Every such description/definition  is different, and goal-oriented approach and consensus building becames essential for the sucess  of your project (MRUS) . 

More information are included in: TOGA Systemic Approach to the Global Specification  - Sophocles Project Report, 2002 (pdf)

6. Conclusive remarks ( but not the final)

-  Every, even most abstract concepts  have been constructed bottom-up basing on human experience  but  therefore their applications have to be done top-down in the real-world abstracion hierarchy.

-  Notions of abstract concepts are based on human  socio-cognitive consensus concentrated around of a "shared utility". It is also valid for the previously discussed concepts, as meta-ontology.
For example,  is it possible to assume arbitrarily  that meta-ontology is an open continuously growing set of axioms  (?) 

- We have to remember,
 

- From  the TOGA perspective, the difference between meta-ontology and meta-epistemology relies on the initial axioms arbitrarrely assumed, usually in an implicie manner (here, a web page in preparation).

- In the both cases we need to use  IPK conceptualization framework to the conceptualization of ontology and epistemology of  intelligent entities

- Definition-making Paradigm

- Results of the Google search illustrate current applications of the above discussed basic terms: 
: "knowledge definition" , "cognitive knowledge",  ontology, ... 
  15/07/2004:  for: knowledge, ontology, preferences, information.   20 300 docs 
  but from the cognitive  perspective, for "cognitive knowledge", ontology. only 164 docs. 

 -  Information, Preferences, Knowledge paradigm:  IPK conceptualization

The examples of:
-  a psychological point of view:
"Contemporary cognitive psychology ignores both epistemology and ontology. A claim which is commonly made is that the science of cognition is concerned with the psychological machinery that enables human beings to have the mental faculties they do. Most cognitive scientists maintain that what enables mental functioning is knowledge, and thus a major aspect of cognitive research concerns the psychological structures and processes that presumably are constitutive of our knowledge of the world. Knowing as such, however, is not a topic of investigation. In other words, that knowledge of the world is achieved is taken for granted. Neither this fact nor the manner in which it comes to be or the source of its veracity are being dealt with. All these topics are relegated to epistemology, and as such, are taken to be outside the scope of psychology proper. This disconcern of epistemology is often regarded as a main difference between scientific psychology and theoretical philosophical analysis. The eschewing of ontology is even more extreme. As far as the scientific psychologist is concerned, ontology pertains to speculative metaphysics. Essentially, like many other scientists, modern students of cognition assume a simple naive realism coupled with an autonomy of the mind relative to it. Cognitive scientists are concerned with the structures and processes of the minds of human being, not with anything outside."[Shanon, B. (2002) "Cognition, Epistemology, Ontology" in Psycoloquy e-journal]
and
- Meta-epistemology meaning by John McCarthy, 2000,  Stanford U. - Comment: here we also may start to discuss the differences between epistemology and ontology.

Links related to the TOGA meta-ontology pages, see:
- Meta-ontological assumptions - definitions framework: http://erg4146.casaccia.enea.it/wwwerg26701/gad-dict.htm
- High-intelligent paradigms:  http://erg4146.casaccia.enea.it/HID/HI-def.htm
as well: The basic paper about TOGA and Abstract Intelligent Agent (pdf)