Semantic Validation in M2M Systems for Data Accuracy
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Solution Overview
Problem
In Machine-to-Machine (M2M) systems, the lack of semantic validation for semantic description resources leads to inaccuracies in semantic description information, affecting the accuracy of semantic queries and reasoning, and hindering data sharing between applications.
Innovation Solution
A method and apparatus for implementing semantic validation in M2M systems, where a gateway stores semantic description resources and an M2M platform stores ontologies, enabling semantic validation using referenced ontologies to ensure accuracy of shared resources and data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If semantic description resources are added to enable data sharing between applications, then data sharing capability is improved, but accuracy of semantic description information deteriorates due to lack of validation
Solution Approach 1:
The patent performs semantic validation as a preliminary action before semantic description resources are registered or used. The validation process checks consistency with ontology references in advance, ensuring that only accurate semantic descriptions are accepted into the system, thereby preventing accuracy deterioration while maintaining data sharing capabilities
Solution Approach 2:
The patent implements a feedback mechanism where validation results are returned to indicate whether semantic description resources pass consistency checks. This feedback loop allows the system to reject or correct inaccurate semantic descriptions, maintaining high accuracy while enabling broad data sharing between applications
2Measurement precision
If semantic validation is implemented to ensure accuracy, then measurement precision is improved, but device complexity increases due to additional validation processes
Solution Approach 1:
The patent introduces an intermediary validation component that mediates between semantic description resources and the ontology repository. This intermediary performs automated consistency checks using ontology references, ensuring accuracy while keeping the overall system architecture modular and manageable, thus limiting the increase in device complexity
Solution Approach 2:
The validation mechanism is designed as a universal component that can validate multiple types of semantic description resources against their respective ontology references. By creating a multi-functional validation system that handles various resource types through a common process, the patent avoids proportionally increasing complexity for each additional validation requirement
Data Source
AI summary
A semantic validation method, applied to a Machine-to-Machine Communications (M2M) system, where the method includes receiving, by an apparatus storing a semantic description resource, an operation request related to a first semantic description resource, including semantic information of the first semantic description resource, an association relationship between the first semantic description resource and another semantic description resource, and a uniform resource identifier (URI) of an ontology referenced by the first semantic description resource, determining that the first semantic description resource is associated with the semantic description resource, sending a semantic validation request message to an apparatus that stores the ontology referenced by the first semantic description resource. Hence, accuracy of a resource and data shared between industries and applications using a public capability of the M2M system can be ensured in a case of no priori knowledge.