Modular Semantically Integrated System Modelling

Abstract

AbstractIn current practice, we engineer systems using modular, composable components. However, when we model systems in languages such as SysML, we build a single model of the entire deliverable system (such as a radio telescope). Though the model is of course hierarchical, consisting of multiple levels of description, these are not quite independent models that can be composed modularly. For example, if we acquire a power supply off‐the‐shelf, ideally we would like the supplier to provide us a model of the power supply that can be integrated into our overall system model, reflecting the same concerns involved in integrating the power supply into our solutions. If we have distributed teams, can they create separate models that are composable? Can model integration be the early version of system integration?This paper discusses how modelling can support modular composability using roles: placeholders for other entities that the entity being modelled depends on in order to deliver its targeted behaviour. All the necessary assumptions relating to the role are captured as role profiles. Model composition then involves binding these context roles to models of actual concrete entities that fit the assumptions. Our paper presents an illustrative example of compositional modelling of a radio telescope, and discusses some of the issues involved in binding. It goes further to indicate how these system models can be linked to relevant domain knowledge frames, and also linked to observations of the system behaviour. The result is a SystemMap: modular, composable knowledge‐centric models that enable capture of all the information and knowledge relating to a system, linked by a network of semantic relationships that enable internal consistency checking, as well as model and knowledge refinement based on consistency with observed real‐world behaviours.