A traditional engineering paradigm is very hierarchical in nature. To understand a whole, first understand the parts then combine the knowledge into an understanding of the whole.
In a noemic paradigm, the understanding of the whole comes first. The understanding of the part is a projection of the whole. The noemic paradigm reflects life.
This section [#!Burback:1997NOEMA!#] proposes that modern software engineering built for highly distributed computing environments should be based on a noemic paradigm.
Life is an example of a Noema. A Noema is not a neural network which simulates the learning process of the brain. A Noema is not a genetic algorithm which simulates system evolution. A noemic paradigm is represented by the body chemistry of living systems like the respiratory, circulatory, immune, and digestive systems.
This section will define the foundations of the noemic paradigm, give some examples, and support the conjecture that a Noema, though harder to build, supports change.
In a Noema, the whole is greater than the sum of the parts.