by Hugh M. Lewis

The methodological/operational basis of systems theory and method are the development of coherent representational models, in a variety of forms, that serve to accurately represent structural patterns, properties and principles of real systems. It is through the construction, development and refinement of representational models that we gain greater understanding of the structural patterns of systems of all kinds, and it is these models that are eventually applied in the development of new systems or in the progressive control of change and moderation of established systems.

All models are primarily conceptual and symbolic constructs in our minds, that are worked in some form in reality. The basis of all art and artistic creativity in human systems is in the development of representative models of reality, in some media or set of media, that are tied to conceptual models and frameworks of understanding or seeing the world.

Modeling and heuristic representation of real or ideal systems in the form of models provides an exploratory and experimental platform of the development of alternative systems by means that are relatively economical and efficacious in terms of cost of resources input into the creation of such systems, and the potential heuristic outcomes and benefits coming from such systems. Construction, prototyping and testing of models is a standard practice in most engineering efforts, and is always a precursor to the actual development of a real system.

Supercomputing has permitted a level of authentic virtual representation of extremely complex systems in a manner that is true and reliable, and has itself constituted a major technological advancement for the sciences, especially in those areas dealing with intrinsically complex data-sets and systems, like meteorology or ecology.

We may recognize certain design principles that might be appropriate to the construction and development of systems-based models relevant to our further understanding of real or ideal systems. We must distinguish in this regard between what can be referred to as general design principles that are appropriate across and for all kinds of systems, and what might be referred to as "system specific" or particular design principles that are appropriate of only a given kind or particular system to which we are referring.

Clearly it is the case that scientific domains have largely emerged around a distinctive body of knowledge and technical/technological methods used to access and augment this knowledge. We cannot conceive of the field of microbiology without a microscope, and we would be hard pressed to articulate a meaningful astronomy without access to even a rudimentary telescope. We must learn to recognize and appreciate the unique differences and specialized assets relevant to each field and domain of scientific research, and to consider these as a part of a larger collection and body of tools available to extend our knowledge of reality in systematic ways.

It is equally clear as well that principles and theoretical models that are appropriate for one area of knowledge or domain of scientific research, do not necessarily translate very well into any other areas or domain of scientific endeavor. The models that apply upon physical levels of stratification in natural systems are completely different than the systems-based models that apply upon biological or human systems levels. 

General Systems Essays, Vol. I