Borrowing techniques from complex systems and software engineering, this paper defines a Functional Modeling Framework to provide a simple common mechanism for representing models of consciousness or cognition that is independent of assumptions made by any specific model. All models of consciousness or cognition should of course fit into the complete set of functions of what consciousness, or cognition can do. Through attempting to represent all such functions (both computable and non-computable), this framework attempts to gain the capacity to represent all models of consciousness or cognition, even where the implementation mechanisms of those functions are unknown. Enabling different models of consciousness or cognition to be more easily compared is intended to enable research on consciousness and cognition to more reliably converge on a single understanding, even across massively collaborative research projects spanning multiple disciplines. Furthermore, if biological functionality can be considered as dynamically stable where it is persistent, then in aiming to provide a common approach for representing and comparing the functionalities of consciousness or cognition as dynamically stable systems, this framework provides a set of features through which it may be possible to see commonality between the functional components of a wide range of other dynamically stable biological or non-biological systems. If such commonality does exist, and if, as proposed, that commonality reflects deeper underlying physical and mathematical principles, then representing any researcher’s model of consciousness or cognition within this framework might help reveal applications of that researcher’s model across a wide range of other domains of study.