## 5 Discussion  
MBSE is a noteworthy, computer-aided approach to facilitate the increasingly complex systems development. However, a rigorous and effective use of MBSE remains challenging. This paper demonstrates some MBSE usability aspects by offering a direct observation on a generalized application. Specifically, it demonstrates how DSM can be used in tandem with GPM to advance these aspects and promote industrial MBSE usability. The introduction of DSM ontology-related constructs and notations was shown to relax the modeling effort required by prospective users, and to increase the modeling rigor. Our demonstration explicitly manifests the effectiveness of using ontologies in systems engineering, addressing the need highlighted by a recent state-of-the-art review [30] as well as the state of the practice [29]. We provided evidence for the significant implications of OPM's ontological clarity deficiencies--deficiencies that were previously only theoretically identified--to OPM's modeling practicality. Specifically, it was shown that OPM features redundancy that requires cognitive effort from its user--to select from multiple permissible modeling alternatives while modeling--which may lead to idiosyncratic, incomparable models. While some modeling alternatives are syntactically correct according to OPM, they are not necessarily ontologically desirable (or even semantically valid) and may risk the rigor of the model. Consequently, this may break the consistency of the information that is kept in the models as well as reduce the ability to analyze the completeness of models with respect to the modeling intentions (for example, by describing the same process differently in various levels of hierarchies or by allowing unspecified states to go unnoticed in process models, respectively). By restricting the allowed syntax of OPM based on DPD domain ontology (of PROVE), we were able to narrow down multiple modeling options (Figures 2-8) to a singular \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Number of Elements in** & **Number of Elements** & **Ratio of Number of** \\  & **OPM Model (Rigorous** & **in PROVE Model** & **Elements between** \\  & **Model Based on PROVE)** & & **OPM and PROVE** \\ \hline Case 1 & 41 & 11 & 3.73 \\ \hline Case 2 & 74 & 28 & 2.64 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Summary of results. pattern, only to find its GPM semantics to be incompatible. We then used PROVE's DPD domain ontology once again to devise a semantically valid pattern, composed of multiple GPM notational elements (Figure 10). In the conclusions of [PERSON] et al. 's report [43], the authors suggested that modeling rules may solve OPM's clarity deficiencies and recommended future research with respect to this. Here we have successfully demonstrated how such rules--in the form of a domain-specific syntax used as a modeling pattern--may indeed help, by completely neutralizing the cognitively demanding, modeling-related user decision making. This significant reduction in available modeling tactics when using DSM compared with GPM, with no loss of details in resulting models, confirms our first hypothesis. We also demonstrated how a domain-specific representation can be used to enhance the ontological clarity of OPM models. A prominent manifestation of this is the OPM visual representation of the composite-state modeling-construct (Figure 10), which violates the acknowledged design principle of one-to-one correspondence between symbol and concept [28]. It is unlikely to demand a process modeler to find such a mechanism on his/her own, nor to implement it consistently in different situations and equivalently to other modelers. This is a crucial issue for MBSE application, as it is a root cause for the idiosyncrasy of resulting models, which revokes potential advantages of applying MBSE, such as promoting reuse and analyzing models comparatively. Correspondingly, the number of elements in the OPD becomes significantly large compared to its conveyed ontological content when using such compound constructs.