Graphical Mapping Tool with ECA Rules for Schema Transformation
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Solution Overview
Problem
Conventional data transformation techniques, such as custom-coded solutions and off-the-shelf products, are expensive, difficult to adapt, and require extensive programming, especially when dealing with multiple data sources and complex schema mappings, and lack support for event-driven transformations and hierarchical data structures.
Innovation Solution
An improved schema mapping language and graphical mapping tool that uses a graphical interface with data and control links, including Event-Condition-Action (ECA) rules, to create and control schema mappings between multiple sources and targets, supporting event-driven and hierarchical data transformations with minimal custom programming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If custom-coded solutions or off-the-shelf products are used for data transformation, then data transformation functionality is achieved, but implementation cost and complexity increase significantly
Solution Approach 1:
The patent introduces an intermediary schema mapping language that serves as a mediator between source and target schemas. This mapping language acts as a standardized intermediate representation that simplifies the transformation process, avoiding the need for complex custom-coded solutions while maintaining reliable data transformation functionality across different data sources and formats.
Solution Approach 2:
The patent segments the data transformation process into distinct components: source schema definition, target schema definition, and schema mapping relationships. By breaking down the transformation into these manageable segments, the system reduces implementation complexity while maintaining functionality, allowing each component to be independently defined and combined.
2Adaptability or versatility
If conventional mapping tools are used, then basic schema mapping is achieved, but support for event-driven transformations and hierarchical structures is lacking
Solution Approach 1:
The patent introduces dynamic event-driven capabilities to the schema mapping language, allowing transformations to be triggered and controlled by events. This dynamic extension enables the mapping tool to handle event-driven transformations and hierarchical structures without requiring a complete redesign, maintaining ease of use while increasing adaptability.
3Manufacturing precision
If manual coding is used for schema mapping, then precise control is achieved, but programming effort and time consumption increase
Solution Approach 1:
The patent enables the schema mapping language to define its own syntax and structure, making it self-descriptive and self-configuring. This self-service capability allows the system to automatically generate transformation logic from the mapping definitions, eliminating the need for extensive manual programming while maintaining precise control over the transformation process.
Data Source
AI summary
Graphical mapping interface embodiments and method are provided for creating and displaying a schema map, which may be used by a data transformation system to perform a data transformation between at least one source schema and at least one target schema. According to one embodiment, the graphical mapping interface may comprise a source schema region for displaying a graphical representation of at least one source schema, a target schema region for displaying a graphical representation of at least one target schema, and a mapping region for displaying graphical representations of a plurality of links connecting the source nodes displayed in the source schema region to the target nodes displayed in the target schema region. The plurality of links may comprise at least one control link having at least one ECA rule associated therewith and at least one data link having at least one textual-based target field expression associated therewith.