Linear Complexity Growth for Exponential Effectiveness
Through Effective Knowledge Resource Entitlement, Modeling, Management, and Sharing
- Reality:Knowledge is reality, as reality is only what is known about it: knowledge.
- Complexity:The need and will to manage the infinite richness, complexity, and evolution of knowledge and reality, distributed as they
are, into all that exists, is the prime computing system, and problem solving, complexity factor, the next being the inabilities
to properly address the issues, especially through the use of ill-founded and ill-grounded knowledge architecture paradigms.
- Phenomena:Yet, as evolution has clearly shown, knowledge is a naturally occurring phenomenon, around which all thinking and minds developed.
- Evolution:Evolution itself could not happen, if knowledge wasn't constantly being accumulated and built upon, from the very fabric of
the universe and Cosmos.
- Architecture:As science has systematically demonstrated, natural phenomena is structured through natural logical architecture and principles.
- Science:Scientifically understanding these architecture and principles has always proven to be the true enabler for all related applications.
- Knowledge:The same is true for the natural phenomena of knowledge.
- Strategy:Accordingly, this document section briefly introduces some natural knowledge structuring principles, briefly considers how
some crucial applications build on these principles, and, backed by a structured set of related standards specifications,
and existing working tool and applications, considers new most advanced applications, as well as how to better ensure linear
system complexity growth, while developing application sophistication, depth, refinement, relevance, structure, effectiveness,
and efficiency exponantially, through effective knowledge-architecture-based design and knowledge resource entitlement, modeling,
management, and sharing, with parallel streaming-content transformation pipelines.
- References:A reference section offers complementary information, links, indexes, and a glossary of knowledge-architecture-related terms.
Knowledge, Architecture, Reality, Resource, Relation, Entitlement,
Modeling, Management, Sharing, Complexity, Collaboration,
Distributed, System, Content, Privacy, Security,
Phenomenon, Nature, Cosmos, REMMS.