Automated Schema Generation via Centralized Artifact Repository
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In large organizations, the complexity of data architectures and redundancy in data model development lead to inefficiencies, such as resource consumption and knowledge concentration issues, which hinder rapid application development and deployment in CI/CD environments.
Innovation Solution
A system for automated generation of data schemas using a centralized artifact repository, graphical user interface, and various formats like JSON, XML, and RDFa, allowing any team member to design and manage schemas without specialized knowledge, enabling rapid development and reducing redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If data specialists manually design data architectures and logical systems, then knowledge quality and schema accuracy are improved, but knowledge concentration risk increases and development time extends
Solution Approach 1:
The system pre-generates multiple schema variations automatically before human review, allowing data specialists to evaluate and select from ready-made options rather than creating schemas from scratch. This preliminary automated generation reduces development time while maintaining accuracy through expert review of pre-prepared schemas.
Solution Approach 2:
The system creates copies of existing data models and schemas, allowing teams to duplicate and adapt proven schemas for new applications. This eliminates redundant work while maintaining schema quality through copying of validated structures, reducing both development time and knowledge concentration risk.
2Adaptability or versatility
If data specialists manually create schemas for each application, then schema customization is improved, but redundancy increases and resource consumption grows
Solution Approach 1:
The system generates copies of existing data models and schemas that can be reused across multiple applications. This eliminates redundant manual creation of identical schemas while maintaining customization through selective modification of copied structures, thereby reducing resource consumption.
Solution Approach 2:
The system creates universal schema templates that can serve multiple applications simultaneously. A single data model can be instantiated and adapted for different purposes, reducing the need to create separate schemas for each application and thereby reducing overall resource consumption while maintaining adaptability.
3Manufacturing precision
If a fixed number of data specialists handle schema development, then knowledge quality is improved, but team productivity decreases and CI/CD pipeline speed is hindered
Solution Approach 1:
The system enables team members to generate their own schemas automatically without requiring data specialists to manually create them. This self-service capability distributes schema generation across the team, improving productivity while maintaining quality through automated consistency checks and expert review processes.
Solution Approach 2:
The system prepares schema options in advance automatically, allowing team members to quickly select and customize schemas without waiting for data specialist availability. This preliminary preparation removes the bottleneck of specialist availability while maintaining knowledge quality through structured review processes.
4Reliability
If data specialists are required for all schema generation tasks, then schema reliability is improved, but ease of operation deteriorates and access complexity increases
Solution Approach 1:
The system allows any team member to generate schemas independently through automated tools without requiring data specialist intervention. This self-service approach improves ease of operation while maintaining reliability through automated validation and expert review mechanisms that ensure schema quality.
Solution Approach 2:
The system introduces an automated intermediary layer between team members and schema generation. This intermediary handles the complex technical work automatically, making schema generation accessible to non-experts while maintaining reliability through structured processes that incorporate expert knowledge without requiring expert involvement in every task.
Data Source
AI summary
A system for automated generation of a schema based on a plurality of artifacts is provided. The system includes a centralized artifact repository storing the artifacts and metadata characterizing each artifact and a computing device. The computing device performs operations including receiving user input indicating an application container, obtaining, from the repository, the metadata for artifacts of the plurality of artifacts, providing, via the display, the metadata, receiving a user selection of an artifact of the plurality of artifacts for inclusion with the application container, storing the application container in association with the selected artifact in an application repository, receiving a schema request related to the application container, obtaining a schema format selection, based on the request, generating a schema based on the schema format selection, the application container, and the artifact associated with the application container, and providing the schema in the selected schema format.