|M.Sc Student||Bolshchikov Sergey|
|Subject||Creating a Spatio-Temporal Dynamic Model from an|
Object-Process Methodology Based Model
|Department||Department of Industrial Engineering and Management||Supervisor||Professor Dov Dori|
|Full Thesis text|
Modeling plays an increasingly important role in the lifecycle of systems. Complex dynamic systems are difficult to model, preventing users from deeply understanding their intricate behavior. Existing conceptual modeling languages contain behavioral diagrams aimed to describe how the modeled system changes over time. However, most of these diagram types are static and do not directly reflect the system’s behavior in space and time in a manner that is close enough to conceived reality. Models that are inherently visual and dynamic can potentially provide system architects and designers, as well as prospective customers, with profound understanding of the behavior of the system under development without requiring knowledge of any specific modeling language. Based on this conjecture, which is supported by cognitive neuroscience, this research has enabled creating Vivid OPM?a spatio-temporal model, which can be perceived as a video clip of the system under development in operation, extracted from and based on its OPM conceptual model. The OPM simulation process provide the formal foundation for spatio-temporal animation by controlling occurring processes, creation and consumption of objects, and changes in object states. This animated model has been shown to be helpful for understanding and communicating complex system dynamics. Comprehension is enhanced by decreasing the abstraction level of the models of those systems and bringing their dynamic aspect closer to reality. The animated model is made more concrete by actually playing what the conceptual model expresses formally but not very intuitively. Particularly, this improves the understanding of complex interaction involving many objects. Evaluation of Vivid OPM with information systems engineering students has shown that it indeed enhances model understandability, especially in complex situation where interactions are involved.