Semantic Engine Mapping SPARQL to REST for M2M Interoperability
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Solution Overview
Problem
Conventional machine-to-machine systems lack the ability to perform semantic queries using SPARQL due to the absence of triplestore-based databases, which limits their capacity for semantic information handling and interoperability with legacy systems.
Innovation Solution
A method and system that enable semantic querying by annotating semantic information into a hierarchical resource structure format, using a semantic engine to map SPARQL queries to RESTful commands, allowing for semantic search and compatibility with existing ETSI M2M systems without requiring a triplestore database.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If semantic information is annotated into the ETSI M2M resource format, then semantic interoperability is improved, but the system cannot perform semantic queries using SPARQL because it does not use triplestore-based databases
Solution Approach 1:
The patent introduces a semantic engine as an intermediary component that sits between the machine-to-machine application and the ETSI M2M database. This semantic engine translates SPARQL semantic queries into RESTful commands that the ETSI M2M system can understand and execute, enabling semantic querying capability without requiring conversion to a triplestore database. The semantic engine acts as a mediator that bridges the gap between semantic query requirements and the existing ETSI M2M architecture.
2Adaptability or versatility
If the entire ETSI M2M system is converted to use triplestore database, then full semantic technology capabilities are enabled, but compatibility with legacy ETSI machine-to-machine systems is lost
Solution Approach 1:
The patent segments the system into distinct functional layers: the existing ETSI M2M database layer remains unchanged to maintain legacy compatibility, while a new semantic engine layer is added on top to provide semantic querying capabilities. This segmentation allows the system to gain semantic technology capabilities through the added semantic engine layer without modifying or replacing the underlying ETSI M2M database, thus preserving compatibility with legacy systems.
Solution Approach 2:
The patent performs preliminary action by adding semantic annotation capabilities to the ETSI M2M resource format before any database conversion is attempted. By annotating semantic information into the existing resource format and adding a semantic engine layer, the system prepares to support semantic technologies while maintaining the original database structure, thereby enabling future semantic capabilities without losing legacy compatibility.
3Adaptability or versatility
If RDF format is used to annotate semantic information, then flexible decomposition of knowledge is enabled, but semantic queries cannot be performed because the system lacks semantic information understanding capability
Solution Approach 1:
The semantic engine serves as an intermediary that not only translates queries but also provides the semantic information understanding capability that the ETSI M2M system lacks. When RDF format is used to annotate semantic information, the semantic engine interprets this structured knowledge representation and enables semantic search by translating SPARQL queries into operations that can search and understand the annotated semantic information in the ETSI M2M database.
Data Source
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AI summary
The present invention relates to a method for semantically querying a database by a machine-to-machine application, wherein the database comprises hierarchically structured resources, wherein semantic information is annotated to at least one resource, and wherein the following steps are performed for querying the database: a) Issuing a semantic query for the database, b) Analysing the semantic query by a semantic engine, c) Translating the analysed semantic query by the semantic engine into one or more queries satisfying a communication protocol of the hierarchical resource structure of the database and d) Providing the translated one or more queries to the database for providing a query result. The present invention further relates to a system for semantically querying a database and to a database.