Qualitative Analyses of Semantic Interoperability Approaches: Toward Learning based model transformations

Abstract

The emergence of cyber-physical systems and connected objects is helping to increase the technical complexity that enables the integration and the collaboration of information systems. This highly heterogeneous digital environment, subject to constant change, requires both the improvement of companies’ capacity for change and the rapid and effective expansion of their digital organization in a flexible and agile manner. In a rapidly changing industrial context, ensuring, and maintaining the digital continuity of information at all levels of the company becomes a major challenge from an economic, technical, and organizational perspective. To meet Industry 4.0 requirements for agility, flexibility, and responsiveness, a "plug- and-play" approach that breaks away from fixed norms and standards seems to be the solution to promote sustainable and on demand interoperability of systems. In this paper, the specifications of the “plug-and-play” are presented. Thus, a qualitative comparison is made between the ontology approach and the Model-Driven-Engineering approach. The goal is to compare their ability to ensure semantic interoperability of systems, and thus digital continuity, based on the criteria of genericity, dynamism, connectivity, integration, and federation capability.