Differential
Ontology Framework
Proposed National Project (US)
to create the
Principles:
Semantic Web technology falls
into two major schools of thought
a) The First School of Semantic Science stipulates that ontology supports common sense reasoning with the imposition of constraint logics like OIL (Ontology Inference Layer for RDF – Resource Description Framework).
b) The Second School of Semantic Science stipulates that ontological models enable knowledge sharing, which can best occur with minimal dependency on constraint logics and inferences based completely on algorithms.
Glass Bead Games on issues related to instrumentation of the Semantic Web.
Simple Point of View: Ontology mediation of human knowledge sharing assumes no role for deduction or other types of logical inference. Ontology is simply a means to form community consensus and to make explicit some “sufficient” set of constructions. Thus the, so-called, descriptive and expressive logics are to be loosely held and formative, in the sense that the logical entailments are constructed not at design time but in real time, or not at all. What is left is a dictionary with the elements of a managed, or controlled, vocabulary whose definitions are encoded into a key-less hash table.
Research à :.:
Note1: The
What creates language, and mathematics, is our ability to create, and remember abstractions.
Note2: The “second school” major vendor components, identified in the BCNGroup Roadmap, have design elements that make second school software human centric. These design elements are reflected in our claim that IT consulting projects, like the 1.6 B dollars electronic Customs Project (eCP) project, is 100% about time and materials related to software development.
Note3: The 80-20 condition is one that is about how humans are and how reality is. This condition creates the need for standard IT consulting projects to be 80-20, 80% active participation by the “client”, and 20% software development. The 100% time and materials accounting for software development is a mistake.
Note4: Government and industry clients feel know the need to have agile and modifiable ontological models. They know that these semantic map systems are required to achieve critical functions of government and industry.
Note5: The procurement behaviors and industry activity wants to continue to act as if IT design and deployment is 100% software engineering. Huge and very costly IT modernization projects will continue to fail until we as a society recognize that Heaven on Earth is here.
Note6: The American people
have more than enough money to develop the types of semantic mapping technology
that Customs, DHS, etc absolutely needs to elevate world wide standards of
living while preserving and extending the principles of freedom and wealth
through democracy.