On the Architecture of Systemology and the Typology of Its Principles (original) (raw)
Related papers
Towards a Structure for Systems Engineering Research
Proceedings of the 15th INCOSE Annual International Symposium – Systems Engineering: Bridging Industry, Government and Academia, Rochester, New York, USA, 10-14 July, CD-ROM paper 6.1.1., 2005
This paper discusses the need for the development of a framework for Systems Engineering to facilitate recognition of Systems Engineering as a discipline and to provide a fundamental basis for advancing the practice of Systems Engineering. Systems Engineering concerns the development of systems that satisfy the real needs of those who call for the systems to be created. Such systems are not tangible things that can be analyzed as objects to be inspected and described, but rather these systems interact with their users and stakeholders in a complex manner, where the introduction of the system perturbs the pre-existent situation, resulting in a need for sophisticated methodologies to analyze and predict outcomes of system creation and deployment. The paper exposes and discusses a range of research methodologies that are appropriate for contributing to the development of a coherent framework of research in Systems Engineering.
A Structure for Systems Engineering Research
Systems Engineering/Test and Evaluation Conference, 27-29 October, Canberra, 2003
This paper discusses the need for the development of a theoretical framework for Systems Engineering to facilitate recognition of Systems Engineering as a discipline and to provide a fundamental basis for advancing the practice of Systems Engineering. Systems Engineering concerns the development of systems that satisfy the real needs of those who call for the systems to be created. Such systems are not tangible things that can be analysed as objects to be inspected and described, but rather systems interact with their users and stakeholders in a complex manner, where the introduction of the system perturbs the pre-existent situation, resulting in a need for sophisticated methodologies to analyse and predict outcomes of system creation and deployment. The paper exposes and discusses a range of research methodologies that are appropriate for contributing to the development of a coherent framework of Systems Engineering.
Systems theory: a formal construct for understanding systems
International Journal of System of Systems Engineering, 2012
In the 2011 issue of this journal, we proposed that "The application of systems theory and systems thinking to the design and management of complex systems of systems and their associated life cycles can provide a valuable lens for the emerging methods in system of systems engineering (SoSE)" (Adams, 2011). Since that time we have had the opportunity to develop an axiom set that we feel is a sufficient construct for systems theory . In this paper, we will explain the multi-disciplinary theoretical foundation and discipline-agnostic framework we have developed for systems theory. We believe that this construct may be posited as a general approach to understanding system behaviour.
A Conceptual Model of Systems Engineering
INCOSE International Symposium, 2018
Systems engineering is widely perceived as an empirical discipline, with a need for theoretical foundations that can facilitate reasoning about practice. This is an attempt to help build such foundations by systems-theoretic inquiry into the nature of the relationship between knowledge and engineering. We conceptualize this relationship in terms of four worlds: the real world, the world of systems models, a world of aspect knowledge, and a world of wholes knowledge: knowledge that indicates how aspects come together and also how wholes relate to each other. This leads us to a generative understanding of systems engineering: synthesizing aspects to develop blocks; and generating the network of blocks that form a system, through recursive performance of three activities: decomposition, dependency closure and refinement. The problem of systems engineering practice involves augmenting this core with the concerns of problem formulation, design of the supporting ecosystem, and the need for closing gaps between the model world and real world. We derive some initial confidence in the validity and value of this strawman model by examining its ability to explain some aspects of current systems engineering practice, and the insights it provides into how we can integrate system modeling across knowledge domains. Introduction: Objectives and Motivation System engineering applies to various domains, enterprise application domains such as banking and insurance, and engineering domains such as infrastructure and operations. Systems engineering as a discipline is responsible for bringing multiple such domains together into a unified system that addresses a set of objectives. A central issue in systems engineering, therefore, is how knowledge from various domains come together to generate a system. Over time, engineering has developed a fabric of concepts about the nature of systems. This includes the notion of blocks (modules, components, subsystems, systems) with structures (entities with attributes, relationships among them, and operations that can be performed on them), and processes (sequences of operations) enabled by these structures that produce behavior. It also includes the notion of block composition, and associated concepts such as interfaces, dependencies, and interactions between blocks and their context. This is a general fabric of concepts that applies to all systems, thereby enabling the discipline of systems engineering, and an associated body of practice knowledge about how to engineer systems that have desired characteristics. Systems theory and systems science have delved deeper into the nature and behavior of systems, leading to concepts such as variety, dynamics and emergence, and bodies of knowledge about the nature and types of systems, relationships between structure, processes and behavior, and the behavior of networks of processes. We also have bodies of knowledge in scientific domains, enterprise (human endeavor) domains such as telecom and medicine, technology domains such as power electronics and scripting languages, and aspect domains such as security, chemistry and performance that focus on particular kinds of system characteristics and properties.
Systems Research and Behavioral Science, 2019
In this paper, I argue that the fragmented state and uneven maturity of current systems science will render it increasingly inadequate for meeting the future needs of the engineering and practice disciplines depending on it. I explain that it is not the case that System Science is a holistic discipline in contrast with the reductionism of classical science, but that Systems Science has both reductionistic and holistic dimensions, dealt with respectively by two "movements" within systems science, which I will designate as "Complexity Science" and "Systems Research". I argue that in many situations the internal workings of a system can be satisfactorily addressed with the mainly reductionistic methods of Complexity Science, whereas when external factors play a significant role, the mainly holistic methods of Systems Research are brought to the fore. This suggest that Complexity Science and Systems Research are not really as disjunct as often portrayed, but represent special cases under a wider conception that would hold across a spectrum of ratios between 'internal complexity' and 'external complexity' of the system of interest, and that would entail a differential emphasis on reductionistic and
Systems Theory as the Foundation for Understanding Systems
Systems Engineering, 2013
As currently used, systems theory is lacking a universally agreed upon definition. The purpose of this paper is to offer a resolution by articulating a formal definition of systems theory. This definition is presented as a unified group of specific propositions which are brought together by way of an axiom set to form a system construct: systems theory. This construct affords systems practitioners and theoreticians with a prescriptive set of axioms by which a system must operate; conversely, any set of entities identified as a system may be characterized by this set of axioms. Given its multidisciplinary theoretical foundation and discipline-agnostic framework, systems theory, as it is presented here, is posited as a general approach to understanding system behavior.
Systems Research and the Quest for Scientific Systems Principles
Systems, 2017
Systems Research formally originated in the 1950s, but a scientific understanding of systemness is still nascent. This shortcoming produces significant risks for complex systems engineering and practice. Current "systems principles" are qualitative heuristics, and systems science is scientific more in attitude than because of any grounding in systems principles employing clear and quantifiable concepts. In this paper, I propose that a model of how principles and laws are understood across the specialized sciences can, when applied to systems science, open up new ways to discover systems principles. This approach has led to the identification of six new avenues for discovering systems principles. In this paper I explain one of these research avenues (which leverages the maturation profile of the specialized sciences) in detail, and reference active projects to pursue others. The research approach advocated in this paper has the potential to lead to a new perspective on the nature of and relationship between systems science and systems engineering.
A Disciplinary Field Model for Systemology
Translational Systems Sciences
The field of systems is still a nascent academic discipline, with a high degree of fragmentation, no common perspective on the disciplinary structure of the systems domain, and many ambiguities in its use of the term "General Systems Theory". In this chapter we develop a generic model for the structure of a discipline (of any kind) and of disciplinary fields of all kinds, and use this to develop a Typology for the domain of systems. We identify the domain of systems as a transdisciplinary field, and reiterate proposals to call it "Systemology" and its unifying theory GST* (pronounced "G-S-Tstar"). We propose names for other major components of the field, and present a tentative map of the systems field, highlighting key gaps and shortcomings. We argue that such a model of the systems field can be helpful for guiding the development of Systemology into a fully-fledged academic field, and for understanding the relationships between Systemology as a transdisciplinary field and the specialized disciplines with which it is engaged.