Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Decision recommendations are a set of alternative options for clinical decisions (e.g., diagnosis, prognosis, treatment selection, follow-up, and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a “reasoning over domain” approach for the generation of decision recommendations by gathering and inferring conclusions from production rules. In order to rationalize our approach, we present a specification that will sustain the logic models supported in the knowledge bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey toward the solution of the reported needs. The starting point of our approach is the proposition of Reflexive Ontologies (RO). Here, we go a step further, proposing an extension of RO that includes the handling and reasoning that production rules provide. Our approach speeds up the recommendation generation process.     

SELF-ORGANIZATION OF LIVING SYSTEMS: A FORMAL MODEL OF AUTOPOIESIS

ABSTRACT

A formalization, computerization and extension of the original Varela-Maturana-Uribe model of autopoiesis is presented. Autopoietic systems are driven by sets of simple “rules” which guide the behavior of components in a given milieu. These rules are capable of producing systemic structures that are far more complex than we could ever achieve by a direct arrangement of components, i.e., by a method of systems analysis and design. The study of autopoietic systems indicates that the traditional emphasis on internal qualities of system's components has been misplaced. It is the organization of components, rather than the components themselves (or their structural manifestations), that provides the necessary and sufficient conditions of autopoiesis and thus of life itself. The dynamic autonomy of autopoietic systems contrasts significantly with the non-autonomous, allopoietic mechanistic systems.     

Organizations as self-organizing and sustaining systems: a complex and autopoietic systems perspective

Many alternative theories about organization exist. Despite this, or perhaps because of it, adequate explanation of the relationship between macro and micro processes of organization, and organizational dynamics remains elusive. In the recent past there has been growing interest in two areas of systems science that offer a different basis for understanding the generative and dynamic qualities of organizations. These are autopoietic theory and complex adaptive systems theory. In this paper, we outline a theory of organization built on a synthesis of these two theoretical strands. It is argued that the approach provides an improved framework for understanding the nature and dynamics of organizational phenomena, and as such a more rigorous basis upon which to base future organizational research.     

AN ARISTOTELIAN SOLUTION TO THE PROBLEM OF SOCIAL AUTOPOIESIS

This paper addresses the problem of social autopoiesis. We argue that to date no adequate solution to the problem of social autopoiesis exists and put this down to the lack of an adequate conception of a social autopoietic unity. We present such a solution based on our reconstruction of autopoiesis theory in a synthesis of Aristotelian/Maturanian metaphysics. From this we derive what we call the Enterprise model and test it against the six-point key of Varela et al. (1974). In light of our solution we then move to a consideration of further problems that may still cast doubt on the legitimacy of the notion of autopoiesis in the social domain. We conclude by arguing that such considerations are in fact groundless and do not materially affect our claims as to the autopoiesis of social systems.     

Life as we know it

This paper presents a heuristic proof (and simulations of a primordial soup) suggesting that life—or biological self-organization—is an inevitable and emergent property of any (ergodic) random dynamical system that possesses a Markov blanket. This conclusion is based on the following arguments: if the coupling among an ensemble of dynamical systems is mediated by short-range forces, then the states of remote systems must be conditionally independent. These independencies induce a Markov blanket that separates internal and external states in a statistical sense. The existence of a Markov blanket means that internal states will appear to minimize a free energy functional of the states of their Markov blanket. Crucially, this is the same quantity that is optimized in Bayesian inference. Therefore, the internal states (and their blanket) will appear to engage in active Bayesian inference. In other words, they will appear to model—and act on—their world to preserve their functional and structural integrity, leading to homoeostasis and a simple form of autopoiesis.     

INTERNAL SOCIETAL REACTION TO EXTERNAL CHANGE: THE CASE OF THE KOREAN PENINSULA

Abstract

As social systems increase in complexity, they must monitor the relationships among their internal components carefully, to see that their functioning is harmonious. The internal components must not only meet their own needs, but must meet the overall needs of the total society as well. If this is not done adequately, the society could face an alarming increase in internal entropy, to its great peril. However, in attending to internal needs, the complex society cannot neglect the need to monitor and reart to a variety of external flows, including monetary and information flows. This paper combines social entropy theory and autopoiesis theory to analyze the relationships between internal and external relations in a complex social system. South and North Korea are used as illustrations. An important issue is how a nation's boundaries are controlled. This is discussed briefly, and five models of boundary control are presented. North Korea is shown to have a model 1 system, while South Korea has a model 4 system.     

SOFTWARE ENGINEERING DESIGN METHODOLOGIES AND GENERAL SYSTEMS THEORY

Abstract

The relation between Software Engineering and General Systems Theory is explored. They are found to be dual meta-disciplines which need each other. It is discovered that there is a simple connection between the background variables of Klir's GSPS and Software Design Methodological Viewpoints. This connection motivates a look al the ontological assumptions underlying the two meta-disciplines which underlies the epistemological framework of GSPS. That framework is used to attempt to understand the nature of the different manifestations of software. This leads to an in depth look at the essence of software which in turn leads to the extension of the epistemological lattice of GSPS. The article shows the complex ways in which Software Engineering Methods and General Systems Theory intertwine al the ontological and epistemological levels which causes us to understand both differently than we would have understood them separately. The point of the article is to show how these two meta-disciplines need and intimately involve each other at a fundamental level and in fact co-arise from each other in spite of the fact that one is extremely general and the other extremely concrete. The object is to establish a basis for software engineers and general systems theoriests to learn from each other based on a common framework for understanding Software Systems     

Information and meaning: foundations for an intersubjective account

Abstract. Information is fundamental to the discipline of information systems, yet there is little agreement about even this basic concept. Traditionally, information has been seen as 'processed data,' while more recently soft, interpretive approaches have taken information to be 'data plus meaning.' This paper provides a coherent and consistent analysis of data, information, meaning and their interrelations. It is particularly concerned with the semantic and pragmatic dimensions of information, and integrates the work of Maturana and Habermas into a framework provided by Dretske's theory of semantic information. The results show that meaning is generated from the information carried by signs. Information is objective, but inaccessible to humans, who exist exclusively in a world of meaning. Meaning is intersubjective — that is, based on shared agreement and understanding — rather than purely subjective. Information, and information processing systems, exist within the wider context of meaning or sense-making and the IS discipline needs take account of this.