Collaborative Semantic Graph for Heterogeneous Data Integration
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Solution Overview
Problem
Current data integration solutions focus on technical mappings and federated access as a single step, failing to address the evolving nature of data integration and the need for continuous monitoring and refinement of data mappings and relationships in semi-structured data environments.
Innovation Solution
A system and method for collaboratively editing and visualizing data using a semantic graph, where data is imported, analyzed, annotated, and stored in a database, allowing multiple users to access and present data in various views based on annotations, with a graphical user interface and server configuration for data sources, enabling continuous refinement and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data integration is performed as a single one-shot step using technical mappings and federated access, then initial data integration is achieved, but the system cannot support continuous refinement and evolution of data mappings and relationships
Solution Approach 1:
The patent transforms the static, one-shot data integration process into a dynamic, evolving system. Users can continuously monitor, refine, and update data mappings and relationships through a graphical interface. The system supports iterative improvement where mappings are not fixed but can be adjusted over time based on user feedback and changing requirements, enabling the integration process to adapt and evolve continuously.
2Productivity
If multiple users need to collaboratively edit and refine data mappings, then continuous improvement of data integration is enabled, but system complexity and coordination requirements increase
Solution Approach 1:
The patent segments the collaborative work into individual, manageable tasks. Each user can work on specific data mappings, relationships, or annotations independently through the graphical interface. The system divides the complex collaborative process into discrete editing units that can be assigned, tracked, and completed independently, then integrated into the overall data model without requiring constant coordination between all users.
Solution Approach 2:
The system acts as an intermediary that manages collaborative interactions. It provides a centralized platform where multiple users can contribute to data mappings and relationships, automatically handling conflicts, version control, and integration of contributions. The intermediary system coordinates user actions behind the scenes, allowing productive collaboration without exposing the underlying coordination complexity to users.
3Ease of operation
If data from heterogeneous sources is integrated into a unified storage, then data accessibility is improved, but data quality and relationship accuracy may deteriorate without continuous monitoring
Solution Approach 1:
The patent implements feedback mechanisms that allow users to monitor the quality and accuracy of integrated data from heterogeneous sources. The system provides interfaces for reviewing data mappings, relationships, and annotations, enabling users to identify and correct errors. This continuous feedback loop ensures that data quality and relationship accuracy are maintained even as data from multiple sources is integrated into the unified storage system.
Data Source
AI summary
Disclosed is an exemplary computer program application, system and method for a unified approach to managing data from heterogeneous sources. The system includes a central, semantic data storage basing on a directed labeled graph model, a module for accessing data sources by drawing access and mapping configuration from the data storage and loading the resulting data into the data storage and a unified user interface that treats each graph node in the data storage as a separate term, visualizes and modified the term's context in the data graph using configurable user interface widgets.