RDF Mapping Rule Generation with Semantic URI Patterns
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tools for converting relational data into RDF format, such as D2R, generate URIs that are meaningless and require manual modification to express relational data features, leading to tedious labor for complex databases with numerous mapping rules.
Innovation Solution
A method and apparatus for generating a mapping rule that includes a URI pattern expressing features of relational data, parsing this rule, and determining pattern matching between relational models to automatically generate a second mapping rule for converting data into RDF format, thereby reducing manual modification workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If a mapping rule is automatically generated using existing tools like D2R, then the conversion from relational data to RDF format is achieved, but the generated URI is meaningless and cannot express the features of the relational data
Solution Approach 1:
The patent changes the parameters of URI generation by incorporating relational data features (table names, column names, data types) into the URI pattern. Instead of using only automatic generation with simple identifiers, the system modifies the URI structure to include semantic information from the relational schema, thereby expressing data features while maintaining automated generation capabilities.
2Loss of information
If manual modification is performed on the mapping rule to express features of relational data, then the URI can represent data features, but much tedious manual labor is required for complex relational databases with hundreds of mapping rules
Solution Approach 1:
The patent performs preliminary action by automatically analyzing the relational database schema and pre-generating feature-expressive URI patterns before the actual data conversion. The system extracts table and column metadata, constructs meaningful URI templates, and prepares mapping rules in advance, eliminating the need for tedious manual modification during the conversion process.
Solution Approach 2:
The system enables self-service by allowing the mapping rule generation process to automatically express relational data features without human intervention. The tool analyzes the relational schema itself, generates appropriate URI patterns based on the data structure, and produces complete mapping rules that capture data features autonomously.
3Productivity
If the URI pattern is simplified for automatic generation, then the mapping rule generation is efficient, but the generated URI cannot express the features of the relational data
Solution Approach 1:
The patent makes the URI pattern multi-functional by designing it to simultaneously serve as an automatic generation template and a feature expression载体. The universal pattern incorporates placeholders for table names, column names, and data types, allowing it to generate unique feature-expressive URIs for different relational structures while maintaining a consistent automated generation process.
Data Source
AI summary
A method for generating a mapping rule for converting relational data into RDF format data includes obtaining a first mapping rule for converting relational data in a first relational database into RDF format data, wherein a URI pattern of the first mapping rule expresses features of the relational data in the first relational database; parsing a generated rule for the URI pattern of the first mapping rule; determining that a second relational model of the second relational database and a first relational model of the first relational database conform to pattern matching; and generating a second mapping rule for converting the relational data of the second relational database into RDF format data, based on a mapping relationship between the generated rule and the pattern matching of the first relational model and the second relational model.