Gaining IIoT insights by leveraging ontology-based modelling of raw data and Digital Shadows

Along a production value chain, huge amounts of diverse data are generated. A proper collection, transfer and modeling of this data is essential for its meaningful use in following engineering tools and applications. Data engineering is thereby complex due to a high variety of possible use cases and a lot of different interpretations of the same data. In this paper, we present an approach to a use case sensitive modeling of raw data by the methods of ontology-based data access (OBDA) and the concept of Digital Shadows. The developed approach is based on an industrial use case of glass production in the Saint-Gobain Sekurit enterprise. Existing data modeling structures of Saint-Gobain Sekurit are extended by an ontology-based application for building use case specific data templates. The aim of this paper is to highlight potentials of semantic data modeling to apply the concept of Digital Shadows for data engineering in the production environment.