Graph-Based Data Validation Framework for Complex Nested Criteria
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Solution Overview
Problem
Conventional data validation approaches lack the capability to validate data using complex validation expressions and do not support nested validation, falling short in ensuring data compliance with various requirements.
Innovation Solution
A graph-based evaluation framework is constructed using node-based connected components, where each node is associated with a validation expression, allowing for complex Boolean operations and nested validation, to evaluate data sets based on specified criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional validation rules are used, then data validation can be performed, but complex validation expressions and nested validation cannot be supported
Solution Approach 1:
The validation system is segmented into multiple independent nodes, where each node represents a specific validation rule or expression. These nodes can be individually configured, executed, and combined to form complex validation workflows, enabling both simple and complex validation scenarios without increasing overall system complexity.
Solution Approach 2:
The patent introduces a graph-based dimensional structure for validation, where validation rules are organized in a multi-dimensional graph space rather than linear sequences. This allows nested validation and complex expressions to be represented as graph traversals, adding a structural dimension that enables sophisticated validation without proportionally increasing complexity.
2Reliability
If simple validation rules are applied, then validation can be performed quickly, but comprehensive data compliance cannot be ensured
Solution Approach 1:
The validation system implements nested validation structures where validation rules can contain other validation rules within them, similar to nested dolls. This allows complex compliance requirements to be broken down into hierarchical layers of validation, ensuring comprehensive data compliance while maintaining manageable complexity through structured nesting.
Solution Approach 2:
The patent combines multiple validation rule types and expression formats into a composite validation framework. Different validation mechanisms (rules, expressions, constraints) are integrated into a unified graph structure, creating a composite validation system that ensures comprehensive compliance while leveraging the strengths of each individual validation approach.
3Adaptability or versatility
If conventional validation approaches are used, then basic data type validation can be performed, but complex validation scenarios cannot be handled
Solution Approach 1:
The graph-based validation node structure is designed as a universal framework that can handle multiple validation scenarios through a single unified mechanism. The same node structure supports simple type validation, complex expressions, nested validation, and various data formats, making the system highly adaptable while maintaining ease of operation through consistent interface and execution model.
Data Source
AI summary
Systems and methods are provided for determining a request to validate data, the request specifying validation criteria; generating a graph for validating the data, the graph including at least one node-based connected component that evaluates the data, the node-based connected component being constructed to represent the validation criteria; validating the data using the generated graph, wherein the data being validated is evaluated by the node-based connected component; and providing information describing the validated data.