# Improving Conceptual Modeling with Object-Process Methodology Stereotypes
## 1 Introduction  
As system complexity is on the rise, there is a growing need for standardized building blocks to increase the likelihood of these systems to succeed. The realization and recognition in recent years that models can and should become the central artifact in engineered systems' lifecycles has become commonplace, giving rise to model-based systems engineering (MBSE) as an evolving systems engineering (SE) field. Conceptual modeling is the primary activity required for engineering systems to be understood, designed, and managed. Modeling languages enable describing the requirements and design of systems in a formal yet understandable way. Increasingly, the paradigms of Internet of Things (IoT) [1, 2, 3, 4], Industry 4.0, [5] System of Systems [6, 7], and Internet of Robotic Things (IoRT) [8, 9] are gaining momentum. In these systems, software modules are embedded in the hardware components, control them, and communicate their status in near real-time via the Internet, relieving humans from mundane operations and serving their personalized needs accurately and more efficiently. As the trend of weaving software components into hardware ones accelerates, the need for a holistic approach, methodology, and framework for end-to-end systems development becomes ever more apparent. MBSE has become the leading systems engineering (SE) paradigm, and it has provided SE with a hitherto sorely missing formal facet. Conceptual modeling is the primary activity required for engineering systems to be understood, designed, and managed. Thisunderlying MBSE process precedes, or should precede, mathematical, physical, geometrical, and disciplinary modeling. Using model-based approaches has numerous benefits, including reduction of risks, early error detection and prevention, team communication enhancement, traceability, and an explicit methodology for reasoning about the modeled system [10; 11; 12]. MBSE is not just about modeling; it is SE that produces a formal conceptual model which serves as MBSE's comprehensive underlying blueprint--the reference artifact that constitutes the source of authority of the various system aspects: requirements, performance, functionality, structure, dynamics, and many other physical and informational (cybernetic) aspects. To achieve this level of authority and trust, MBSE requires a rigorous conceptual modeling methodology, which encompasses a universal ontology, a language, a set of principles and guidelines, and an enterprise-wide supporting modeling software environment. Object-Process Methodology, OPM [13; 14; 15], is a holistic formal yet intuitive approach, language, and methodology for the representation of knowledge and the development of complex systems. The OPM language is bimodal--it uses both graphics and text to represent knowledge at various, interconnected levels of detail about the two major aspects of any system: structure and behavior. This bimodal representation caters to humans' dual channel processing--the first of the three assumptions of the cognitive theory of multimedia learning [16; 17], which states that there are two separate channels for processing information: the auditory and the visual. The two other assumptions of the cognitive theory of multimedia learning are that (1) the capacity of the channels is limited, and (2) learning is an active process of filtering, selecting, organizing, and integrating information. OPM is designed with these three cognitive assumptions [18]. It accounts for the second assumption by its top-down hierarchical decomposition via abstraction-refinement mechanisms, reducing cognitive load [17]. The third assumption is taken care of by engaging the modeler in actively organizing and linking model elements, and by visually executing (simulating) the model to gain deep understanding of the dynamic aspect of the knowledge it represents.