Data Broker System for Semantic Preservation Across Formats
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Solution Overview
Problem
Traditional data representation models fail to efficiently interoperate between different services and applications due to differences in serialized and in-memory data formats, leading to challenges in maintaining data semantics and requiring manual documentation and code conversion.
Innovation Solution
A broker system utilizing a novel syntax and modeling language that supports rich semantic mechanisms like inheritance and constraints, generating code to transform data between various representations while preserving semantics, using a syntax as a broker between multiple data representations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional data representation models are used, then data can be stored and transmitted efficiently, but data semantics cannot be preserved when transforming between different services and applications
Solution Approach 1:
The patent introduces an intermediary data model that acts as a broker between different data representations. This intermediary model preserves data semantics by maintaining a canonical representation with explicit type definitions, constraints, and relationships, while enabling transformation to various target formats without losing semantic information.
Solution Approach 2:
The patent segments the data transformation process into distinct components: a source data model, an intermediary semantic model, and target data models. This segmentation allows each component to be optimized independently while maintaining semantic fidelity through the intermediary layer.
2Adaptability or versatility
If different serialized and in-memory data formats are used for different services, then each service can be optimized for its specific requirements, but manual documentation and code conversion are required
Solution Approach 1:
The patent implements self-service through automated code generation. The system automatically generates transformation code and documentation based on the intermediary data model, eliminating the need for manual conversion and reducing human intervention in the data transformation process.
Solution Approach 2:
The patent performs preliminary action by pre-defining the intermediary data model with all semantic information before transformation occurs. This pre-established model serves as a template that guides automatic code generation and transformation, saving time during actual data interchange operations.
3Productivity
If serialized data is optimized for specific storage or transmission use cases, then storage and transmission efficiency is improved, but the fundamental logical model of the data is obscured
Solution Approach 1:
The intermediary data model serves as a mediator that maintains the fundamental logical model while enabling optimized serialization for specific use cases. It preserves type definitions, constraints, and relationships that would otherwise be lost in optimized formats, allowing round-trip transformation without information loss.
4Adaptability or versatility
If manual code conversion is used between different data representations, then flexibility in handling different formats is achieved, but errors increase and efficiency decreases
Solution Approach 1:
The system performs self-service through automated transformation code generation. By generating code automatically from the intermediary model, the system maintains flexibility in handling different formats while eliminating manual errors and improving transformation efficiency through consistent, machine-generated code.
Data Source
AI summary
An approach is provided for data modeling and code generation. The approach involves, for example, providing a syntax for generating a model representing data and semantics of the data. The approach also involves providing an architecture configured to accept the data according to any of a plurality of data representations. The approach further involves providing a code generator configured to generate computer code to transform the data between the plurality of data representations by using the model as a broker between the plurality of data representations. The code generator preserves the semantics of the data during the transforming of the data.