Self-Describing Data Model for Recursive Query Integration
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Solution Overview
Problem
Current search technologies face challenges in implementing recursive searches on data expressed in certain markup languages stored in relational databases, particularly due to difficulties in formulating and executing recursive queries and the inability to support query functionality across dynamic data models, leading to errors when the database schema changes.
Innovation Solution
A query engine is developed for recursive searches in a self-describing data system, which generates a representation of a federated system using logical model items, enabling communication between client and third-party systems by mapping item types and connection information to facilitate data retrieval and integration across different data models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If recursive search queries are implemented on relational databases, then search functionality is provided, but the complexity of formulating and executing queries increases significantly
Solution Approach 1:
The patent introduces an intermediary layer (the system architecture with data access layer, business logic layer, and presentation layer) that mediates between the user's search request and the complex database operations. This intermediary handles the complexity of recursive queries internally while providing simple search interfaces to users, thus resolving the contradiction between providing search functionality and maintaining ease of operation.
2Adaptability or versatility
If the database schema is changed to support dynamic data models, then adaptability improves, but query execution reliability deteriorates due to schema validation errors
Solution Approach 1:
The patent implements dynamic data models that can adapt to changing schemas without breaking query execution. The system uses dynamic typing and flexible data structures that can accommodate schema changes while maintaining query reliability. This allows the system to be adaptable to new data formats while ensuring that queries continue to execute reliably even when the underlying schema evolves.
3Adaptability or versatility
If multiple computer-implemented systems are integrated, then data communication capability improves, but system complexity increases
Solution Approach 1:
The patent creates a universal integration framework that can communicate with multiple different computer-implemented systems through a common interface and data model. This universal layer handles the complexity of integrating different systems internally, while presenting a unified, simple interface to users. The system can adapt to various external systems without increasing visible complexity, thus resolving the contradiction between improved data communication capability and increased integration complexity.
Data Source
AI summary
In one embodiment, a computing device includes a computer-implemented system configured to generate a logical model item type in a self-describing data model implemented by the computer-implemented system, wherein the logical model item type defines a schema of an external object model implemented by a third-party computer-implemented system executed by a third-party computing device, the logical model item type comprises a logical model type (LMT) item type representing data of the third-party computer-implemented system. The computer-implemented system is configured to generate a mapping item type in the self-describing data model, wherein the mapping item type defines a mapping between an item type of the external object model and the LMT item type. The computer-implemented system is configured to use the mapping to enable data communication between the computer-implemented system and the third-party computer implemented system.