Digital Twin Data Broker with Assisted Mapping into a Knowledge Base

The frequent usage of digital twins to communicate between physical objects is resulting in more complex cyber-physical systems. To simplify the individual components’ integration and to optimize their usage, a data broker is being developed. Therefore, digital twins need to be semantically organized in an ontology that provides the advantage of reasoning methods. An assisted workflow is being developed to automatically enter subgraphs into an ontology. As a digital twin representation, the Asset Administration Shell format is used to have an international standard technology. Based on this, a new domain-specific language is developed, allowing experts to configure the generation process. This process maps the digital twin’s information into a graph representation of the ontology. The preconfigured generation process enables the user to efficiently register new digital twins without having expert knowledge of the underlying ontology. Additionally, a Large Language Model vector embedding and text reasoning support is implemented analysing the digital twin to create entity suggestions. The presented data broker is an automation tool for bridging the gap between semantic descriptions and digital twin formats in order to unite the advantages of both representations.