OWL-to-OPC UA Model Mapping for Semantic Interoperability
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Solution Overview
Problem
Current industrial automation control systems lack a method for transforming amended OWL ontologies back into their originating graph-based information models, particularly in OPC UA XML format, hindering end-to-end semantic interoperability.
Innovation Solution
A method and transformation unit that retrieve and express node classes and semantic descriptions from OWL ontologies into a graph-based information model, using mapping rules to convert OWL to OPC UA XML, including parent node identification, reference modeling, and modeling rules, enabling reverse transformation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If OWL ontology is used for semantic representation, then semantic interoperability and information retrieval capability are improved, but the ability to process and validate the model on industrial automation servers is worsened
Solution Approach 1:
The patent introduces an intermediary transformation process that converts between OWL ontology format and OPC UA XML information model format. This intermediary transformation layer allows semantic information to be preserved in OWL format while enabling industrial automation servers to process the equivalent information in their native OPC UA XML format, thus resolving the compatibility issue without losing semantic interoperability capabilities.
2Productivity
If unidirectional transformation from information model to ontology is implemented, then semantic analysis capability is improved, but the ability to propagate amendments back to the original model is worsened
Solution Approach 1:
The patent implements bidirectional transformation capability, including the reverse direction from OWL ontology back to OPC UA XML information model. This inversion of the traditional unidirectional approach allows amendments made in the ontology to be automatically propagated back to the originating information model, enabling continuous synchronization and eliminating the need for manual updates.
3Manufacturing precision
If manual mapping of ontology amendments to information model is performed, then transformation accuracy is improved, but time consumption and workload are worsened
Solution Approach 1:
The patent employs automated copying and transformation mechanisms that replicate the structural and semantic relationships between OWL ontology elements and OPC UA XML information model elements. This automated copying process maintains high mapping accuracy by preserving the semantic relationships while dramatically reducing the time and manual effort required compared to manual mapping procedures.
4Adaptability or versatility
If bidirectional transformation is implemented, then end-to-end semantic interoperability is improved, but system complexity is worsened
Solution Approach 1:
The patent implements a universal transformation framework that handles multiple transformation scenarios (OWL to OPC UA XML, OPC UA XML to OWL, amendment propagation, validation) through a unified bidirectional transformation engine. This multi-functional approach achieves end-to-end semantic interoperability while managing system complexity by providing a standardized, reusable transformation infrastructure rather than separate specialized tools for each transformation need.
Data Source
AI summary
Transforming graph-based industrial information models, e.g. OPC UA information models, into a formal semantic representation of an ontology, e.g., an OWL ontology, has proven beneficial for a number of application cases being concerned with information retrieval and processing, such as querying huge industrial information models, validating these information models, providing data efficiently to industrial process analytics etc. The present embodiments are bridging an existing gap in the reverse direction to achieve end-to-end semantic interoperability between an information model as processed on components of an industrial automation control system and an ontology being a formal semantic representation of the originating information model.