Ontology-Based Federated Data Access System
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Solution Overview
Problem
Current data access systems lack semantic interoperability across diverse information sources, making it difficult to provide unified access and management of data across enterprise boundaries, and existing solutions do not effectively handle access rules and resource optimization in federated networks.
Innovation Solution
A distributed, federated system using a grid of agents and gateways that communicate via ontology-based messages, with agents employing logical rules to determine query plans, optimize resource usage, and enforce access policies, while also dynamically managing resource loads and integrating new data sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a federated system integrates multiple diverse information sources, then semantic interoperability and unified access are improved, but system complexity and difficulty of managing access rules increase
Solution Approach 1:
The patent introduces an intermediary layer consisting of agents and gateways that mediate between users and diverse information sources. These intermediaries translate and adapt queries across different data formats and access protocols, enabling semantic interoperability without requiring direct integration between all system components, thus managing complexity through controlled mediation.
Solution Approach 2:
The system segments the federated network into autonomous agents and gateways, each responsible for specific data sources or functions. This modular segmentation allows independent management of access rules for each segment, reducing overall system complexity while maintaining unified access capabilities through coordinated operation of segments.
2Reliability
If access rules are enforced across diverse data sources, then data security and access control are improved, but query processing time and system performance deteriorate
Solution Approach 1:
The patent implements preliminary action by pre-establishing access rules, authentication mechanisms, and authorization policies before query execution. Agents and gateways are pre-configured with access control metadata and credentials, enabling rapid enforcement of security rules during query processing without adding significant overhead to actual data retrieval operations.
Solution Approach 2:
The system employs self-service mechanisms where agents autonomously evaluate access rules and authenticate requests without requiring centralized verification for each query. Gateways automatically manage their own access control policies and credentials, reducing the processing burden on the central system and improving overall query performance while maintaining security.
3Productivity
If resource optimization is implemented in federated networks, then system efficiency is improved, but the complexity of dynamically managing resources increases
Solution Approach 1:
The patent incorporates feedback mechanisms where agents continuously monitor resource usage, query performance, and system load across the federated network. This feedback information is used to dynamically optimize resource allocation, adjust query routing decisions, and balance workload across available data sources, improving system efficiency through adaptive resource management based on real-time conditions.
Data Source
AI summary
A method for data access includes defining an ontology for application to a set of diverse data sources (58) comprising data having predefined semantics, and associating with the ontology one or more logical rules applicable to the semantics of the data in the data sources. Upon receiving a query from a user regarding the data, a query plan is determined for responding to the query by selecting one or more of the data sources responsively to the ontology and by identifying an operation to be applied to the data responsively to the applicable logical rules. A response to the query is then generated in accordance with the query plan.