Semantic Search Path Translation for Database Complexity
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Solution Overview
Problem
Current database systems face challenges such as complexity in relational database creation, inefficiencies in object databases, and limitations in scaling and data representation, particularly when dealing with complex and heterogeneous data structures, which hinder effective data analysis and decision-making processes.
Innovation Solution
The implementation of a system that translates search paths into semantic format, allowing for universal applicability across different data models, utilizing semantic technologies and domain ontology to provide a unified data view, enabling flexible data analysis and visualization without requiring users to be SQL experts, and allowing for real-time data exploration and path reuse.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If relational databases are used to organize data in tables with defined relationships, then data can be accessed easily and less information has to be entered in total, but verifying that relationships are set up correctly becomes time-consuming and complexity arises when numerous tables are involved
Solution Approach 1:
The patent introduces an object definition component as an intermediary layer between the user and the relational database. This component provides a simplified object-oriented interface that automatically handles the complex table relationships and data mapping, allowing users to access data through intuitive object references without manually verifying complex relational structures
Solution Approach 2:
The object server component serves multiple functions: it acts as a translation layer between object-oriented applications and relational databases, provides automatic data mapping, handles concurrent access, and manages relationship verification. This multi-functional approach consolidates what would otherwise require separate complex processes into a single unified system
2Adaptability or versatility
If object databases are used to store complex data and relationships directly without mapping to relational rows and columns, then complex data can be stored efficiently and the system can be programmed with small procedural differences without affecting the entire system, but lower efficiency occurs when data is complex and relationships are complex, and late binding slows down access speed
Solution Approach 1:
The object server acts as a mediator that translates object-oriented data access requests into optimized relational database queries. This intermediary layer maintains the flexibility and adaptability of object databases while leveraging the speed and efficiency of relational database engines, avoiding the performance penalties of pure object database approaches
Solution Approach 2:
The system performs preliminary data mapping and relationship definition through the object definition component, which pre-configures how objects map to database tables and relationships. This preliminary setup enables efficient data access by establishing optimized query paths in advance, avoiding the need for runtime interpretation that causes late binding overhead
3Reliability
If traditional database systems are used, then data can be stored and retrieved using established methods, but difficulties arise in scaling and representing complex and heterogeneous data structures, and effectiveness in data analysis and decision-making processes is hindered
Solution Approach 1:
The patent creates a universal data access layer that can handle multiple data models (relational, object-oriented, hierarchical) and heterogeneous data structures through a unified object-oriented interface. This allows the system to maintain reliable data storage using traditional methods while simultaneously providing flexible access to complex and heterogeneous data through semantic understanding and object references
Solution Approach 2:
The system dynamically changes the parameters of data representation by allowing the same data to be accessed through different object models and relationships depending on the specific analysis needs. The object definition component enables flexible schema evolution and adaptive data modeling without compromising the underlying storage reliability
Data Source
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AI summary
The present disclosure provides a computer-implemented method for applying an analysis to a data model comprising data objects. The method may comprise receiving the analysis and the first data model each in semantic format. Next, the analysis and the data model may be computer processed to (i) identify one or more elements missing from the data model and (ii) determine that the analysis is not applicable to the data model upon identification of the one or more elements. The one or more elements may then be presented to a user for adjusting the data model. This may be repeated until the analysis is applicable to the data model. The analysis may then be performed on the data objects of the data model.