The Nature of Systems
Lead Authors: Randall Anway, Paul McGoey, Curt McNamara, Contributing Authors: Gary Smith
This article introduces The Nature of Systems knowledge area (KA). Whilst the previous sections are concerned with the Introduction to System Fundamentals, or "The Engineering of Useful Artifacts" (Mobus, Kalton 2014); This section aims to illustrate the nature of systems.
Topics
This KA contains the following topics:
Additional articles illustrating general concepts, theories and principles universal to all systems shall be added over time
System World Views
While a broad spectrum of perspectives on concrete systems derives from practices of Systems Engineering (Sillitto, et al) and other systems-centered disciplines, the discipline of Systems Science seeks abstract, generalized, and universally applicable concepts, principles, and theories of systems.
The overarching concept ‘system’ applies to any physical or conceptual subject of interest - including abstract domains of knowledge.
A system is a set of interrelated components. According to Bogdanov, a system (or complex) is not simply a collection, aggregate (or vector) of components and their relationships. A system is a process, or continuous flux of independent component producing processes, concatenated in self-triggering circles of buildup and degradation. Bogdanov's system cannot be separated from its environment, because it does not simply exist or interact with its environment: it is structurally coupled with its environment and thus evolves its own environment while co-evolving with it.
A common observation about systems is that they display properties which are not apparent from the properties of the components themselves. This is sometimes referred to as synergy, or as emergence.
While a system is often perceived as a structure, the systemness comes from the relations between the components within this structure.
In the practice of systems engineering, a system is often identified with its function. The function is a property of the system's behavior, and the system’s behavior is enabled by the structure of the system.
Systems can be both 'physical' and 'conceptual' things. Conceptual things - mental processes - often correlate with physical causes (eg, events observed in brains) and which may be considered to 'constitute' a separate class of relational processes.
If 'conceptual' things can be grounded in relational processes correlated with physical causes, it stands to reason that communicating meaningfully about physical causes at various spatial and temporal scales provides a theoretical basis for including conceptual and physical things in the domain of 'concrete' systems.
In this narrow sense it may be said that all subjects of interest take part in a 'unitary' system of 'concrete' (physical) nature. That is, as an irreducible physical unity, the universe is composed of conceptual and physical things existing in interlocking and subsuming processes of interrelation that may be described in subjectively relatable terms - in other words, 'understood'.
This 'systemness' (existing understandably in relational processes) is a general characteristic of all things. It is not necessarily a specific characteristic of every thing - for example, inscrutably complex things may be regarded as irreducible yet still be considered in relational, systemic terms.
Very broadly, relational processes having to do with physical systems (eg, mechanics) are studied intensively in the realm of physical sciences while those of conceptual systems (eg, ontologies) veer into the realm of social sciences. System Science is concerned primarily with operationally meaningful units generically identified as 'systems' and potentially includes relational processes across domains of scientific concern.
A potentially reconciling theme in this discussion of physical and conceptual categories of relational processes is 'complexity'. Complexity Science provides useful frames of reference for meaningful approaches to both realms generally (eg, physical and social).
Definitions and Problems of terminology
In this overview article we recognize the (apparent) huge body of literature [a google scholar search on "nature of systems" returns 13,000 results] on the nature of systems. While a few basic definitions of systems (Sillitto et al. 2018)) are widely accepted in practice, significant differences in specialized usage exist.
Thus, here we try to use commonly understood terms and if Systems Science uses highly specialized terms we attempt to associate those with System Engineering terms. While potentially useful to consider this diversity in terms of a more broadly organized taxonomy, it's helpful to appreciate that terminology is unlikely be permanently 'fixed' or fully normalized; this contingent relation with human expression is a feature of the universe and dynamic interactions within it.
The dual nature of such contingency is notably paradoxical. On one hand, incommensurate terminology can present problems. On the other: opportunity. Together, in the open-ended relation between 'problem' and 'opportunity', interesting things can occur.
The available knowledge about systems is very rich indeed but it is yet chaotic (the system of system knowledge often yields more questions than answers) and the domain of system science relates variously with many knowledge domains (specializations) in the broader culture. One of the goals of system science, therefore, is to purposively help reconcile such 'geographical' concerns - literally and figuratively. This leads to validating questions of valuation and realization for systems knowledge and systems science pursuits.
Value of systems knowledge
The nature of systems, as one of the most powerful and widely used paradigmatic conceptions is a common thread across all human existence. Generally, systems in the universe do not embody human agency - humans and system scientists do. The validation, legitimation, and valuation of systems knowledge generally occurs in its relation to human (social) systems. More specifically, system science in the service of systems engineering (or vice versa) recognizes and is capable of anticipating and delivering value for system stakeholders - who are typically situated in systems of other derivation.
Systems science (as an activity system) adds value by organizing and tailoring concepts, theories, principles and assets which render useful expressions of fact, concern, effect or degree pertaining to forms, functions, and fitness of systems in the landscape of systems competencies.
These patterns of expression help stakeholders anticipate complex dynamic situations and compose descriptions and sequences of action (eg, plans) in multiple relatable - and reliable - ways. System scientists must communicate with a range of stakeholders in order for systems to be engineered to operate predictably well. In turn, stakeholders must be conversant in the 'local' language(s) of their systemic interest; often this takes priority and the value of system science is in expressing knowledge in terms stakeholders understand rather than the other way around.
Clearly, the nature of systems can be elusive and pursuit of systems knowledge a great challenge. Future articles in this KA are continually being developed to complement (and also improve upon) existing articles. The concepts in the titles of the articles can always be improved upon but the essence of the content should be consistent with this compact description, as it captures foundational themes in our understanding of the relation between human minds and the universe we are present to.
A Set of Systems Concerns
One of the aims of this section is to illustrate the wide array of concerns in systems science literature. Looking across the literature, there is a a notable variety of useful categorical mappings and taxonomies. Here we introduce ten representative concerns of systems science; the list is intended to be illustrative rather than definitive.
- ‘’Identity: Bounded networks of relations among simplified elements constitute a nominal and semantically meaningful unit, pragmatically speaking. This 'systemness' is a general characteristic of all things and can often be represented (expressed) as a non-random (informative) network of symbols.
- ‘’Processes: layers, levels, and dimensions of dynamically changing structure and function.
- ‘’Networks of relations between elements: connectivity, structure, and holistic properties such as resilience, criticality, efficiency.
- ‘’Dynamics on multiple time scales: states and sequences of change such as growth, collapse, cycling, pattern-formation, criticality.
- ‘’Complexity : variability in number of elements and dimensions of element relations including additivity, connectivity, and inter-adaptability (contingency, dependency).
- ‘’Evolution: progression of qualitative, quantitative, and/or semantic change over time.
- ‘’Information: matter and energy 'encoded' within network(s) of relation or exchange between senders and receivers.
- ‘’Governance: modes of mutual regulation and adaptation between elements, typically involving synergetic co-operation or competitive interference.
- ‘’Contingency: degrees of freedom within a network of constraints which the system is subject to.
- ‘’Methods of interaction. Profoundly, every system has a kind of signature; a unique way of showing up to human cognition, through which it reveals or exchanges information and yields knowledge about its state and identity; Practically, this involves (human) stakeholders and their respective processes of attention. In regard to system science and engineering - attention to specific exchanges of energies through bounded interfaces (eg, scientific instrumentation; sensing/measuring systems), rather than narrowing-in on surface experience of limitations and boundaries. In other words, system science is a process of open ended learning.
Gaining a 'feel' for systems
Systems are an ordinary occurrence; we are immersed in systems. It is a challenge, however to discover the unity in the immense diversity of ways systems manifest in experience. Some 'hard won' ways of thinking about systems seem to have been more consequential than others, however. Principles of electromagnetism and thermodynamics have formed much of the basis for industrialized systems, while principles of cybernetics and networks have been foundational for information systems. In mathematics, iterated function systems and complexity science have provided insights into the ontogeny of complex organic forms. An understanding of living systems seems to be served by a complex amalgam of these fundamental insights.
This is by no means a complete landscape of systems concepts, rather it may help to scaffold a useful entry point into the diverse inspirations and instrumental concepts for systems engineering.
References
Works Cited
Bogdanov, A. A. (1996). Bogdanov's tektology. Book 1. Hull, Centre for Systems Studies, University of Hull.
Sillitto, H. Griego, R. Arnold, E. Dori, D. Martin, J. Mckinney, D. Godfrey, P. Krob, D. Jackson, S. (2018). What do we mean by “system”? - System Beliefs and Worldviews in the INCOSE Community. INCOSE International Symposium. 28. 1190-1206. 10.1002/j.2334-5837.2018.00542.x.
Primary References
Capra, F., & Luisi, P. L. (2014). The systems view of life: A unifying vision. Cambridge University Press.
Mobus, G. E. and M. C. Kalton (2014). Principles of Systems Science, Springer New York.
Trefil, J.S., The Nature of Science: An A-Z Guide to the Laws and Principles Governing Our Universe. 2003: Houghton Mifflin.
Additional References
None.