Abstract: A method for querying industrial data amongst a plurality of industrial entities is provided. More specifically, the method is for querying industrial data stored in a triple store, using a transformed query expression, where the triple store includes an aggregated ontology of industrial data. Efficient querying of an aggregated and transformed OPC UA information model is enabled. Query operations imposed to a plurality of industrial entities including skill-matching, onboarding of devices into machinery, and data-mining are allowed to be performed.

Abstract: Providing data generally involves a transformation of an OPC UA data model into an ontology. Such an ontology readily provides desired capabilities for validation, querying, and analytics of the OPC UA data model using sophisticated standard tools adapted to the ontology. A method for transforming a semantically enriched and graph-based data model into a target ontology is suggested. By a first act, identifications of nodes are retrieved of the data model. Subsequently or concurrently, semantic descriptions of one or more references interconnecting one or more nodes are retrieved. These semantic descriptions are expressed by at least one or more predicates and one or more concepts (e.g., classes) in the target ontology to be produced. Eventually, the target ontology is structured by a semantic ontology language and output to a triple store.