This chapter presents a generic system model called URANOS, that allows to design complex human-centered systems. It is not aligned to any particular discipline. Rather, it helps to build integral systems in different domains of science and engineering, even though it was originally intended to participate in the design of complex human-centered systems in the framework of ICT. URANOS aims at encouraging interdisciplinary work and reinforces the understanding of complex systems in general. It combines different epistemological standpoints and their corresponding realities into a wholeness. Concretely, the three fundamental standpoints of objectivism, subjectivism and holism are used to holistically handle all relevant entities such as humans, animals, machines and environments. This chapter also addresses systemic features like consciousness, collaboration and symbiosis providing a generic and abstract understanding of them.
TopAbout Epistemology
Complex systems like living systems, and particularly human beings, can be described from a variety of standpoints. To be able to understand a system as a whole, all these realities have to be taken into account. For example, a person can be described as a physical body, or as a psychic apparatus (Freud, 1993). None of the views are wrong, but none describes the human being completely. To understand human beings all of them must be considered, the body, the mind, and the spirit (Wilber, 2007). The generic approach of URANOS takes on this epistemological insight, in which multiple standpoints and realities can exist in parallel and form a new cosmology.
This approach also leads to the insight that any kind of classification is subjective and incomplete. Subjective, because a classification depends on the standpoint of the observer (e.g. designer, architect, analyst). Incomplete, because no one knows all possible classes, and between two classes an infinite number of other classes could exist, like between two irrational numbers. To manifest these insights, URANOS uses the principle of a spectrum (Gelernter, 1994). While describing our model, just a few aspects on a particular spectrum are presented in more detail, like extrema or endpoints. We implicitly assume that there will be more aspects on that spectrum, but at this stage it does not seem worth mentioning them.