Digital Twin Mapping Strategy Evaluation for Interoperable Data Exchange
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The creation of mapping rules between different digital twin formats for real-world entities is a manual, error-prone process, hindering interoperable communication and requiring extensive knowledge of source and target formats, especially when formats change over time.
Innovation Solution
A computer-implemented method that automatically generates mappings between digital representations of real-world entities by evaluating predefined mapping strategies based on structure and semantics similarity measures, allowing for robust and error-reduced data exchange across different formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual mapping rule creation is used between different digital twin formats, then mapping can be customized to specific format requirements, but the process becomes tedious and error-prone
Solution Approach 1:
The system enables automatic self-mapping between digital twin formats by evaluating predefined mapping strategies and selecting the most appropriate one based on structure and semantics similarity measures, eliminating the need for manual engineer intervention while maintaining high mapping accuracy
Solution Approach 2:
The system changes the approach from manual parameter-by-parameter mapping to automatic parameter mapping by evaluating multiple mapping strategies (such as structure-preserving, minimizing, maximizing, name-based-heuristics, and semantic-references-based strategies) and selecting the optimal one based on similarity measures between source and target formats
2Reliability
If manual mapping creation by engineers is used, then domain knowledge can be applied, but the process requires extensive knowledge about source and target formats
Solution Approach 1:
The system introduces an intermediary mapping strategy evaluation mechanism that automatically assesses multiple predefined mapping strategies (structure-preserving, minimizing, maximizing, name-based-heuristics, semantic-references-based) and selects the most appropriate one, replacing the need for engineer expertise while ensuring mapping correctness
Solution Approach 2:
The mapping process is segmented into distinct evaluation phases: structure similarity evaluation, semantics similarity evaluation, and mapping strategy selection. Each phase handles specific aspects of the mapping problem independently, reducing overall process complexity while maintaining correctness
3Adaptability or versatility
If proprietary digital twin formats are used by different real-world entities, then each entity can optimize for its own requirements, but interoperable communication becomes difficult
Solution Approach 1:
The system provides a universal mapping framework that can handle multiple proprietary digital twin formats (such as Asset Administration Shell, OPC UA, and other industry-specific formats) through a common evaluation and selection mechanism, enabling interoperable communication while preserving each format's unique characteristics and optimizations
Data Source
AI summary
A computer-implemented method for interoperable data exchange between a first real-world entity and a second real-world entity with both real-world entities connected to a same communication network, the first and second real-world entities having first and second digital representations, respectively, each digital representation being a virtual entity replicating data, structure, and functions associated with any one of the real-world entities, the first and the second digital representations having different formats, the method, executed by at least one computing device of the second real-world entity, including: receiving a request for data of the second digital representation to be provided to the first digital representation; evaluating a set of predefined mapping strategies with each mapping strategy being associated with a target model template, by determining a mapping similarity measure for each mapping strategy based on similarities in a structure and semantics of respective data models of the first and second digital representations.