Knowledge Representation Foundations
As languages have proved ineffective to adequately represent knowledge, as presented in
"The Main Language Fallacy",
and since we do need to model, manage, and share knowledge and its architecture,
with the added support of advanced computing systems, we need an effective representation approach.
As language structure, grammar, and syntax are inadequate to represent knowledge,
even if they can be very practical to infer references between communicating parties with common related knowledge contexts,
the knowledge and knowledge architecture representation approaches must be based on and derived from the natural structure
and not the structure of languages.
But, at the same time, representational structures are required, as well as corresponding notation elements.
Symbols, qualification, and relations, for example, need to be defined and expressed, as they are required for languages.
The main differences are in the structure and architecture approaches.
Qualities are the fundamental component of knowledge, as presented in
"Qualities Map Directly To Neural Patterns",
but what are qualities and how can they be expressed and represented in both human and computer accessible ways?
How can everything that can be known be effectively expressed and represented in both human and computer accessible ways?
How can everything that can be known be effectively related, interrelated, and correlated in both human and computer
Conceptually, it is in fact relatively simple, especially as it is natural and intuitive like the natural phenomenon
of knowledge is.
At the core, as everything else are applications of these components, it can be expressed in three basic statements:
- Qualities range from simple to compound, as they can be nested and combined to any degree or level. The most fundamental qualities
are, in order, identification and relation, where classification is also a basic relation application.
- Everything we can know are identifiable quality collections, which we naturally call resources and which encompass and map
all concepts, beings, things, systems, environments, processes, feelings, behaviors, phenomena, and relations.
- Relations are resources like any other, but they also have references to the subject (e.g. source) and object (e.g. destination)
resources that they relate and for which they qualify each relationship.
The following conceptual derivation diagram uses standard UML class diagram notation
to illustrate the required core knowledge architecture representation foundations,
along with the notation components at their base, as well as along with a few basic applicative extensions,
like events, processes, and adaptive cases, for example.
Right Side Up
Note that, possibly contrary to the traditional Object-Oriented approach of putting the more general structures on top
and the more specialized on bottom,
this diagram puts specialization on top and the generalized foundations at the bottom.
Accordingly, the traditional white inheritance arrows are now pointing down to the more general "ancestor" structures.
The main reason for doing so, is that it seems natural that foundations sit below the structures that they support,
and because the applications, modeling, managing, and sharing knowledge, are the main interest and focus.
Knowledge Architecture Foundations, conceptual derivation UML diagram
Better Knowledge Representation Foundations
There is much more to knowledge and knowledge architecture representation,
and much more still to their modeling, management, and sharing, but already,
we have defined much more appropriate foundations than language structures,
for the tasks at hand.