JSON API Metadata Registry with Schema Enforcement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for maintaining data integrity and referential integrity in metadata storage, such as using spreadsheets, are prone to errors and lack effective mechanisms for ensuring accurate relationships between metadata entities and attributes, leading to difficulties in maintaining high data quality and accurate metadata relationships.
Innovation Solution
A metadata repository system utilizing a JavaScript Object Notation (JSON) Application Programming Interface (API) with schema enforcement, configured in a three-tier architecture, that collects and transmits metadata elements while maintaining relationships and integrity, includes quality checks to reject duplicates and incomplete data, and provides alerts for corrections, ensuring only normalized data is entered into the enterprise data registry.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If spreadsheets are used to store metadata elements, then ease of operation is improved, but data integrity and referential integrity deteriorate due to human input errors and lack of validation mechanisms
Solution Approach 1:
The patent replaces manual spreadsheet operations with an automated JSON API system that enforces data integrity through programmatic validation. The mechanical process of manual data entry and relationship maintenance in spreadsheets is substituted with automated JSON schema validation, duplicate detection, and referential integrity checks performed by the API server, thereby eliminating human error while maintaining operational efficiency.
Solution Approach 2:
The JSON API acts as an intermediary layer between local systems and the enterprise data registry. It mediates data transmission by validating metadata elements against predefined schemas, checking for duplicates, verifying referential relationships, and ensuring data quality before allowing entry into the central registry, thus protecting data integrity without compromising ease of operation.
2Reliability
If quality checks are performed on all metadata elements, then data quality is improved, but processing time and system complexity increase
Solution Approach 1:
The patent implements preliminary validation actions by defining JSON schemas that specify required fields, data types, and constraints before data submission. The system performs preliminary checks for duplicate metadata elements and validates referential relationships against existing data in the registry before allowing data entry, thereby ensuring data quality without requiring complex post-processing validation logic.
Solution Approach 2:
The quality check system is segmented into distinct validation components: schema validation for structural integrity, duplicate detection for uniqueness, and referential integrity validation for relationship accuracy. Each validation function operates independently and can be selectively applied based on data type and context, reducing overall system complexity while maintaining comprehensive data quality control.
3Reliability
If JSON API with schema enforcement is implemented, then data integrity is improved, but device complexity increases due to additional validation layers
Solution Approach 1:
The JSON API is designed as a universal interface that handles multiple functions: data validation, duplicate detection, referential integrity checking, and data normalization. By consolidating these functions into a single multi-functional API layer, the system achieves comprehensive data integrity enforcement without proportionally increasing complexity, as the same infrastructure supports all validation operations.
Data Source
AI summary
A method for maintaining data integrity and referential data integrity within an enterprise data registry is provided. The method may use a JSON API to structure incoming data such that the incoming data is only accepted at a central repository when the incoming data normalized and properly referenced. Ensuring the proper relationships within a JSON API may require the use of bridge tables and/or mapping schemes to correctly identify many to many relationships between entities and attributes within metadata elements.