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; 

where:

• 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.

A 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 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:

A 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.