Physical and Conceptual Systems

Systems can be either physical or conceptual, or a combination of both. Systems in the physical universe are composed of matter and energy, may embody information encoded in matter-energy carriers, and exhibit observable behaviour. Conceptual systems are abstract systems of pure information, do not directly exhibit behaviour, but exhibit “meaning”. In both cases, a system’s properties result, or emerge from:

  • the parts or elements and their individual properties; AND
  • the relationships and interactions between and among the constituents, the system and its environment; 


  • a “property” is an attribute, quality, or characteristic of something;  
  • “between” refers to binary interactions or relationships (binary means between two constituents), whereas “among” refers to relationships and interactions involving more than two constituents (in graph theory, such a relationship involving N parts or elements is referred to as “N-ary”);
  • it is often argued that in physical systems we only need to consider interactions, but relationships are also important (e.g. is part of, is assembled to, is vulnerable to, is owned by, costs, weighs….); interactions can be considered as a special type of relationship, but because of their importance in systems engineering, they are mentioned explicitly). 

We can consider the structural ontology of physical and conceptual systems to be the same, at the fundamental level of parts and relationships – this is what allows us to model physical systems using conceptual systems – but the process ontology is quite different. A physical system can perform and manage processes internal to the system; whereas any change to, or use of, a conceptual system involves processes performed by external physical systems interacting with the conceptual system.

Physical Systems

physical system is an arrangement of parts or elements that together exhibit behaviour that the individual constituents do not. (This definition includes biological systems and living systems.) 

Physical systems are composed of matter and energy. Information is embedded in physical systems, and is stored and transported, in matter/energy carriers. The behaviour of physical systems manifests itself as flows and exchanges of matter, energy and information, and interaction through force fields. The emergent property by which physical systems can be identified is that they perform processes to transform matter, energy and information in ways that their individual parts cannot. (NB “physical systems” includes biological and living systems, because they exist in the physical universe.)  

Systems exhibit variable degrees of coupling and cohesion. A physical system may be a single complex object, such as an organism; or an “object aggregate”, a collection of objects that are inter-related in a way that makes them distinct from the rest of the universe. To be considered a system, the collection must exhibit observable properties not exhibited by the parts, separately or in other combinations: typically, transformation processes that cause observable effects, and binding processes that maintain observable cohesion. 

Our knowledge of physical systems is ultimately limited by what can be observed, and is further limited by what observations we have chosen to make. Rosen (2012) explains this very clearly in terms of “the modelling relation” between models and observables. Our (inevitably partial) understanding of physical systems is expressed as models and narratives. (Allen & Starr, 2017)

“Observability” of a real system does not mean it is being, or has been, observed. It simply requires information about the system’s state and effects to be accessible, in principle, to a notional sensor or “meter”. What is observed depends a) on what an “observer” can, and chooses to, measure; b) on the frame of reference used for the observation; and c) (as Allen and Starr (2017) emphasise) on the scale of the measurement. Not all phenomena of interest can be observed directly; in practice, many are observed indirectly, essentially by inference due to cause-effect chaining.

Conceptual Systems

Conceptual systems are composed of information or knowledge. Information in a conceptual system can be stored or transported in a physical system by being encoded into the matter or energy states of the physical system. Thus:

conceptual system is an arrangement of parts or elements that together exhibit meaning that the individual constituents do not. 

A conceptual system is a “knowledge structure” and is composed of information and knowledge elements. The elements of a conceptual system are related to each other but do not interact with each other. The conceptual system interacts with physical systems which create, modify and interpret it. Its emergent property is meaning, as intended by its creator or editor. This depends on the semantics (meaning of the elements) and syntax (meaning of the relationships between the elements). The perceived meaning will match the intended meaning only if the semantics and syntax are shared between creator, editor and interpreter. A conceptual system can help us to interpret the state (past, present, or expected future) of the universe.

A conceptual system only exists as long as it is hosted in a matter/energy carrier, whether that is, for example, a computer memory, a book manuscript, tablets of stone, an idea in a biological consciousness, or information stored in DNA. Once the last record, consciousness or preserved pattern of the concept has disappeared, the concept has disappeared as well. (When the last copy of a book is burnt, the last file deleted, and the last person who read it has died or succumbed to dementia, that “conceptual system” has ceased to exist.)  

Thus, conceptual systems are generated, evolve and decay not unlike physical systems. A practical case in point is computer software, an important kind of conceptual system, where the evolution of the code tends to be accompanied by an increase in entropy until the code becomes unmaintainable. The term “entropy” is often used in this context. The thermodynamic analogy holds well in terms of the increasing effort required to maintain software and keep it working as it becomes more disorganised. 

The appearance or behaviour of physical systems often embodies and conveys meaning. For example, poisonous animals may have distinctive markings as “warnings” to predators, and engineered products convey meaning with labels, the relationships between parts, or provide obvious affordances for interaction. 


Engineered systems include products, services and enterprises. Services and enterprises usually depend on technological products but are essentially forms of socio-technical systems. “Engineered systems” may include hardware, software, firmware, processes, people, organizations, governance structures, information, knowledge, techniques, facilities, services, other support elements, and (usually modified) natural elements.
An important task in the “systems engineering” of engineered systems is therefore to establish or confirm the operational concept: how the system will be used to create value, while avoiding unintended negative consequences.
Thus, Systems Engineering involves both conceptual and physical systems; and engineered systems almost invariably include both physical and conceptual elements. In such cases, an engineered system can be thought of as a physical system and a conceptual system combined.
Even in the case of a pure “physical system”, we make our systems usable, for example, by overlaying
concepts that are embedded in the design as symbols, colors, shapes and other signs that convey meaning to the user on how to use the system, how to turn it on and off, which parts of the system are safe to touch, when is there some condition to be aware of, and so on.
Systems engineering often produces conceptual systems - models of the current “problem situation”, the
perceived problem or opportunity, and the envisaged future solution and the effect it will have on the problem situation.
Once the conceptual model of the proposed solution is demonstrated to have sufficient likelihood of solving or ameliorating the problem situation, that conceptual model becomes the blueprint for the physical system. The conceptual model of the proposed solution can be used as a reference point for the “as intended” system. The physical “as built” system can be compared to the conceptual model, and each may inform the other. The relative timing of the model activity and the build activity will depend on the balance of risk and reward for each project.
Once the physical system is deployed, we examine the effects produced by the system in the real world, and if necessary, update the conceptual models to reflect reality. These updated conceptual models are then used as the basis for changes to the system to meet changing needs and circumstances.
In the context of Systems Engineering, another very important form of conceptual system is the “Process Instruction”. This includes computer software, and also policy and process documents that tell people how to make, use, support and retire the system of interest. A process instruction is a conceptual system; whereas a process is a transformation of matter, energy or information, done to or by a physical system.


In the constructivist worldview, a system is not something presented to the observer, it is something to be recognized by an observer. In such cases, the word “system” does not refer to existing things in the real world but rather to a way of organizing our thoughts about what is real and make sense. This constructivist view of reality states that systems do not exist in the real world independently of the human mind. In this view, a system cannot be understood by analysis of the parts because of their complex interactions and because purpose or meaning can only be perceived in the whole. A system (from this perspective) is in itself always an abstraction chosen with the emphasis on either structural or functional aspects. A system is then anything unitary enough to deserve a name. A system is thus represented by a set of variables sufficiently isolated to stay constant long enough for us to discuss it as a coherent whole. This notion of a system is one way we, as humans, can organize our thoughts about what we see, or conceptualize, about how relationships and interactions between parts or elements result in outcomes.
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