Overview

In previous chapters we have said that systems engineering (SE) defines models that are internal and external, address multiple levels of composition, are general or specific, and define categories or individuals. But how do we state or represent such models, what do the models mean, and how do we communicate about models in such a clear way that we achieve the shared understanding of specifications? The "we" here refers to all agent interactions, in any combination of humans and machines.

That is the focus of this chapter. The conceptualization dimension of the model space is concerned with the content, languages, and meaning of models.

The conceptualization spectrum includes languages (how and ultimately what to represent) and concepts or referents from the problem domain, which ranges over subject areas such as aerospace, transportation, construction, and organizations. It also includes considerations such as the design, analysis, or modeling constructs that will be necessary to solve those modeling problems in the solution space, to the degree of verisimilitude necessary. The heterogeneous subject matter highlights the complicating fact that the model space of SE is fundamentally multilingual and multi-ontological, and must implicitly deal with the necessary mapping from the representation of the problem to the representation of the solution space.

The discussion in this chapter uses concepts presented in Chapters 6 and 7. The multilevel, whole-part structures in Chapter 6 are used to show the structural context for much of the multiplicity of ontologies and languages in SE. The...