Research Group  Meta-Knowledge Engineering & Management Server  (MKEM)


Meta-Knowledge Unified Framework

TOGA (Top-down Object-based Goal-oriented Approach) perspective

 


 Adam Maria Gadomski


 

 Definitions of the top concepts

Knowledge:   every abstract property of human/artificial agent which has ability to process/transform  a (quantitatively /qualitatively) information  into other information (such as: instructions, emergency procedures,  manuals, scientific materials, models, theories).   Every knowledge has its reference domain where it is applicable. It has to include the source  domain of the processed information.

Model-knowledge (or model) is a representation of a domain for a given/assumed  goal with sufficient accuracy.
 
[TOGA Meta-theory]
- For more: TOGA encyclopedic information

Meta- X      :  a  X(D),  where  its subject matter/(domain-of-activity)/(domain of reference)/ (application domain)  D  includes some common properties of another Xs and X. sets.  A  meta-X  is not X generalization perspectives , it may conceptualize X  as an entity from different points-of-view (including a goal-oriented perspective). [TOGA Meta-theory]


  What is meta-knowledge? How it is used?

 

  Numerous discussions dealing with these questions. The term meta-knowledge is possible to interpret as knowledge about knowledge. Meta-knowledge is a knowledge which domain of  reference/application is another specific domain-dependent knowledge.

Meta-knowledge is a more or less intuitive conceptual instrument related to the evaluation, validation and development of theories in every science. It is especially important for such interdisciplinary research and scientific domains as, knowledge engineering, knowledge management which study and operate on universal knowledge properties abstracted from local dependencies and terminologies.

 

The relation meta- enables to construct more than one level of meta-knowledge, and can be divided according the subject of its domain knowledge.

In the case of an intelligent entity (a person, organization,  society  or highly-autonomous robot), metaknowledge includes  rules, methods of planning, modeling, learning and every conceptualization tools that enable modification of a domain knowledge. Subsequently, the procedures, methodologies and strategies of:  teaching, coordination of e-learning courses, changing domain preferences are its/his/her individual meta-meta-knowledge.

From the sistemics perspective,  an universal meta-knowledge theory framework has to be mandatory and valid for the modelling of meta-levels of every individual meta-knowledge.

 

There is useful to notice here that the theories of meta-knowledge which are related to different common properties of a selected class of theories,  are meta-theories (metatheories).

 

A meta-theory  M  may represent  the specific point of view on a certain class or set of  theories T  and this viewpoint generates meta-properties of T. Meta-properties are the consequence of the relation between M   and T, but they are not the  properties of any T application domain.

 

More formally speaking, a theory T of the domain D is a meta-theory if D is a theory or a set of theories. For example, in computer science, the Theory of Data Bases Organization is a meta-theory for every specific (domain-dependent) theory of  data base.

 

  Remarks

  The difference between a general theory and metatheory is defined below.

- General theory is the theory relating to a domain D,  where D = D1 ... Di-1 Di   and certain domains Dj  , for Dj {Di},  may have a specific theory Tj.  In this sense a general theory is  a generalization of  the theories  from  {Tj}.

 

Metatheory  is the theory of a domain DT,  where DT= T1 ... Tk-1 Twith a common  domains D,. and it may refers to the pre-selected class of properties of  DT (selection of the viewpoint).

  For example, the theory of the utility of the certain set of theories is a metatheory.

 

 See also, for ex. "ISSUES WITH META-KNOWLEDGE", 1999, International Journal of Software Engineering and Knowledge Engineering, Vol. 10 No. 4 (2000) 549, http://eprints.ecs.soton.ac.uk/10535/01/99sekej.pdf

 

 

  Top foundation criteria and constrains of the meta-knowledge problem

  Meta-Knowledge Unified Framework (MKUF) has to be a systemic approach to the development of  a  theory about knowledge.

Every MKUF is or has to be, implicitly or explicitly, goal-oriented(/driven/directed/based/....).

On the other hand, from the nature of the problem, results the utility of a top-down ( leading us from a most general perspective to details) approach.

Production and operation on knowledge require some meta-knowledge frameworks for knowledge conceptualization, representation and structuring.

These requirements can be fulfill by the application of an abstract objects world/network as a basic  tool for the mapping of our perception to its  mental "image".

According to the J. Rasmussen (1) and after M. Lind (2) observation, apart of the emotional motivations, every human goal/objective can be initially decomposed on three generalized goals:  production goal, safety goal and economy goal.  They, subsequently, can be seen from different "observation distance" (see the TOGA's generalization levels and methodology). The spectrum of these distances is changed  from the global scale of worldwide politics to the scale of individual knowledge engineers and researches.

 

Meta-knowledge research also covers emergent meta-science fields. Here a top-perspective of meta-knowledge is applied to the searching of common properties of different sciences and the meta-science can be comprehend as a science on sciences. An example on meta-science subfield is methodology of science, which is especially developed in social sciences ( see, for instance: http://cscs.umich.edu/~crshalizi/notebooks/scientific-method.html, and Google search).

 

The next essential element necessary for the construction of a MKUF is a clear separation of the such concepts as: information, preferences, knowledge

 

All the above metacriteria ( criteria for the criteria choice) and axioms were applied to the construction of the Top-down Object-based Goal-oriented Approach (TOGA)  metatheory (1993).

 

We may assume that most general concept which can cover all aspect of knowledge treatment  is Knowledge Management (KM).

Here, from the intelligent entity perspective,  we may distinguish  two principal activities:  Knowledge Production,  and   Knowledge Transfer.

 

  Knowledge Production and Management

On the top generalization level, the goal production of knowledge  is closely connected with and dominated by a society  sustainability objectives and expectations. In the case of a human organization it is subordinated to the individual/group interests of its dominating members, especially in mutual assistance organizations/associations.

As a domination/subordination relation is transitive, not always a maximization of knowledge production or its quality is the effective  top-dominating intervention-goal of knowledge management in human organizations.

 

  Economy and Knowledge Management

In the modern, quasi post-industrial societies, the concept economy ( or knowledge business) influences all fazes of the knowledge production, processing and applications. It refers to the common meta-knowledge modeling bases of knowledge engineering, knowledge management, knowledge research. On the other hand, it is closely related to the socio-cognitive contexts of the interrelations between knowledge managers and their social and personal environment.

The knowledge economy ( economy of knowledge) is not only a hot problem of our society. It can be seen as a critical aspect of:
  -  society education strategies - from the political national perspective - in short and long terms
  -  scientific and technological research management  - in large and local scale,
  -  basic research development in the fields of computer, cognitive and systemic science.
as well as,
  -  SME knowledge business - for example, in the context of the Chinese "invasion" on the European markets.

 

The concept of knowledge business is closely related to emerging Knowledge procurement

( where:  Procurement is the acquisition of goods or services at the best possible total cost of ownership, in the right quantity, at the right time, in the right place for the direct benefit or use of the governments, corporations, or individuals generally via, but not limited to a contract.[Wikipedia] ).

 

- Using TOGA model of personoid, is  easy to see that knowledge procurement is closely related to the  meta-knowledge preferences (first 

  meta level in IPK architecture).


  Knowledge "produce" information,  technologies, services and other knowledge.
  Goal-oriented knowledge builds our preferences, therefore it enables to reduce information overload. In general, utility of tools depends on  

  their economy and this also is valid in the case of knowledge.

 

  Some examples of new approaches to the knowledge management in economy

-    Advancing Public Procurement:Practices, Innovation and Knowledge-Sharing, Conference Call, Rome , Sept. 2006.

-   Scandizzo, P.L. and L. Paganetto, "Post-Fordism, New Economy and the case of the Italian Mezzogiorno "

   in Luigi Paganetto (ed.) Knowledge Economy, Information Technologies and Growth, Ashgate, 2004

-   Luigi Paganetto, Knowledge Economy, Information Technologies and Growth, 2004

...

   Google search: "knowledge economy", "large organizations", 782 docs (26/09/05) and about 13 000 docs one year later.

 

 

  Knowledge Transfer

  Knowledge transfer is a multidimensional activity. It includes different forms of education, learning, as well as, it dealing with human resources acquisition  management and the management of the science and technologies on academic, industrial  and  politics levels.

 

We may notice that all goal-oriented activities dealing with knowledge have to lead to some forms of knowledge transfer from one to the next human generations.

 

  Multi-goal Management

Multi-goal knowledge management is our reality and  our necessity.  It is not yet sufficiently explicitly and directly present in the available research literature ( see below: Google search *, **). In TOGA, it is based on the management of  multi-preferences related to the different domains of activity of human organizations and human individuals. Every intelligent entity constructs its own domain-dependent preferences distributed among organization knowledge managers, not all are common and  more, some their invisible part may be essential for the organization behavior. Therefore domain-dependent preferences  lead to the necessity of different forms of negotiation and the management of " invisible".

A model of multi-goal knowledge management is possible to construct using the TOGA's IPK architecture ( Universal  Reasoning Architecture Paradigm, URAP). as well as   Universal  Managerial Paradigm (UMP).

 

  General References

(1) Rasmussen, J. (1986). Information Processing and Human-Machine Interaction. An Approach to Cognitive Engineering, Amsterdam: North-Holland.

(2) Lind, M. (1990). Representing Goals and Functions of Complex Systems, Tech. Rep. 90-D-381, Department of Automation, Lyngby, Denmark.

....................

 (*) see: Google search:  "multi-goal knowledge management", 0 docs (26/09/05)

 (**) see: Google search: "multi-criteria knowledge management", 0 docs (26/09/05)

F

    Meta-Knowledge Engineering &

    Management Research Server

  Context  > Google search

(26/09/05):

Knowledge production: 363.000 docs 

Knowledge safety:         133.000 docs

Knowledge economy: 1.660.000 docs 

(30/01/06):

Knowledge transfer:    2.650.000  docs

 

 The page has been reviewed by professional editor

1997,2001, ENEA. HID, A.M.Gadomski. All  stuff  may be freely distributed in its full original format, if selected ideas are to be published in another format, a reference to the original source and to the author must be evidenced, intellectual rights reserved. No permission is granted to download and save professional images or any other material from these pages other than for viewing and citation purposes.  These are research pages,  representing the opinions of the contributors, but not necessarily of ENEA.