Knowledge Architect/Overview/Business

Business-Knowledge Architecture & Governance
Definition [J]

Business-Knowledge Architecture & Governance
The effective value of the enterprise is its knowledge, the potential sum of knowledge and understanding of everyone and everything that has ever been contributed to it, or that it has experienced in any way, as well as what knowledge it can infer from this knowledge.

Effectively managing its knowledge is key to the enterprise success, and failure. Issues typically range through acquiring, cleaning, maintaining, digitizing, structuring, modeling, transforming, persisting, indexing, retrieving, presenting, processing, sharing, securing, using, ..., so that this most precious value can adequately blossom in/for the enterprise and its purpose and action.

Current trends tend to define relatively arbitrary initial or reference semantics, irrespective of the natural structure and operation of knowledge.

In fact, it often seems that enterprise knowledge is typically reduced to some rather static information stored in a database reference system, providing some access to some humans.

Ontology can be used to try to better organize and provide access to enterprise knowledge. Ontology provides some common understanding for terms referring to some reality, at some point in time, about which knowledge is to be entered and accessed.

Ontology Model
Ontology Model

In such context, of arbitrary semantics, may they be rather light like in RDF, or heavier with more elaborate ontology, for example, in any case, they are arbitrary or convention-based, even and especially at the root and core concept levels. With roots that are not optimally congruent with the natural structure and operation of knowledge, typically from a lack of understanding of the natural knowledge phenomenon, most enterprise knowledge management is expensive and clearly sub-optimal:

  • Ontology discussion can last for very long time on even basic concepts
  • The representation remains arbitrary, imposing constraints that tend to grow with time and evolution
  • Compatibility and exchange remain difficult, and most of all
  • Computing system cannot contribute at the enterprise knowledge level
  • Making human-system interfaces more limited, increasing complexity
  • Preventing governance and governance automation
  • ...

This domain is vast and cases can differ, but, for a simple example, in a way, RDF, owing much to relational Entities and Relations, defines relations as links, urls to be more specific. where nodes can be attached to try to define the relation type, which is definately insufficient to support effective knowledge relationships, at least natively.

One could try to create complex RDF structures to better reflect a knowledge relationship, only to build more arbitrary monoliths, with worse interfaces, no compatibility, and much increased complexity. OOP, RDF, ontologies and other approaches lack congruence with the reality and knowledge phemomena structure and operation.

Much like Icarius and others trying to fly without a deep enough understanding of the structure and operation of all the implied phenomena including: aerodynamics, fluids, mass, energy, materials, propulsion, etc.

Misunderstanding the natural structure and operation of knowledge has lead to arbitrary foundations, tools, and semantics, often based on the decision of some individual, others to try to fit each's interpretation of its reality, into the arbitrary model available.

Both reality and knowledge are natural phenomena that were not arbitrary created by humans. Properly understanding them is key to trying to manage them.

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