Unified Metadata Model Consolidates Redundant Data
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Solution Overview
Problem
Multiple source metadata models often result in redundant data and incomplete data representation, as unique data is scattered across different locations without a comprehensive hierarchy, making it difficult to manage and integrate effectively.
Innovation Solution
A unified metadata model is generated by selecting and copying classes from multiple source metadata models using a unified metadata mapping, eliminating redundancy and organizing data into an efficient hierarchy, allowing for consistent formatting and future expansions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple source metadata models are used to represent diverse data, then data completeness and versatility are improved, but data redundancy and structural complexity increase
Solution Approach 1:
The patent merges multiple source metadata models into a single unified metadata model by copying and integrating classes from different source models. This consolidation eliminates structural complexity while preserving data completeness by organizing all metadata classes into one coherent hierarchy that can represent diverse data types without redundancy.
Solution Approach 2:
The unified metadata model serves as a universal structure that can represent data from multiple different source models. By creating a single model that incorporates classes from various sources, the system achieves multi-functionality where one metadata model can handle diverse data representation needs without requiring separate specialized models for each data type.
2Reliability
If data is scattered across multiple locations in source metadata models, then specialized functionalities are maintained, but data integration and management efficiency deteriorate
Solution Approach 1:
The patent applies segmentation by organizing the unified metadata model into distinct classes copied from different source models. Each class maintains its specialized characteristics and functionality while being organized in a structured hierarchy. This allows specialized functionalities to be preserved through class-level segmentation while improving overall data management efficiency through centralized organization.
Solution Approach 2:
The unified metadata model acts as an intermediary structure that integrates data from multiple scattered source models. By creating this intermediate layer that copies and organizes classes from various sources, the system maintains the specialized functionalities of individual source models while improving data integration and management efficiency through a centralized access point.
3Loss of information
If redundant data exists in multiple source metadata models, then data completeness is ensured, but storage efficiency and processing speed decrease
Solution Approach 1:
The patent merges redundant data from multiple source metadata models into a single unified structure. By consolidating classes and their properties into one model, the system eliminates duplicate data storage while ensuring data completeness is maintained through the integration of all unique properties from source models. This reduces processing energy requirements by avoiding repeated handling of identical data across multiple models.
Data Source
AI summary
Systems and methods for generating a unified metadata model, that includes selecting a first source metadata model, copying a first class, from the first source metadata model, to a first modified metadata model using a unified metadata mapping, and after copying the first class, selecting a second source metadata model, copying a second class, from the second source metadata model, to a second modified metadata model using the unified metadata mapping, and creating the unified metadata model using the first modified metadata model and the second modified metadata model.