Ontology-Driven Knowledge Modeling and Reasoning for Multi-domain System Architecting and Configuration

Our work is concerned with the development of model-based systems engineering (MBSE) procedures for multi-domain system architecting, configuration, and reasoning. This class of problems is characterized by the presence of multiple domains (which could be cyber, physical, or hybrid), each with their rules and constraints that need to be integrated in a correct-by-design systems and processes in order to satisfy stringent constraints on performance, safety, and effective management of system functionality. To that aim, there is a strong need for formal methods of analysis that can enable effective assembly of components into correct-by-design and provable systems capable of delivering desired capabilities. Thus, this paper discusses semantics and their central role in the development of a new ontology-driven knowledge modeling and reasoning approach for multi-domain system architecting and configuration. Three interdependent modules supporting each other are integrated to make up the system. A foundation module (1) with description logics (DL) as core knowledge representation formalism provides the necessary mathematical foundations to a semantic platform module (2) constituted of semantic blocks (i.e., ontology, rules, and specialized computational capabilities). A configurator module (3) later assembles systems from instantiated semantic blocks as per architectural configurations of interest to generate valid system design alternatives. An implementation of the system on rule-based generation of architectural configurations for satellite robotic arms demonstrates the capability of our approach.