Semantic Data Store Ontology Mapping Business Policy
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Solution Overview
Problem
Businesses face challenges in implementing and enforcing policies across various systems due to the need for technical expertise, as existing solutions require understanding specific application terminologies and lack intuitive interfaces, making it impractical for policy makers without technical knowledge to monitor and control activities across diverse business applications.
Innovation Solution
A method and system that utilize ontologies to map data from one schema to another, optimizing data storage and analysis based on policies, allowing for intuitive policy definition and enforcement across multiple applications without requiring detailed knowledge of each application's technical design, using a semantic data store that organizes data according to business policies and ontologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is stored in multiple different business applications with differing standards and specifications, then the business can operate with specialized applications for specific purposes, but it becomes burdensome for policy makers to learn specific terminology for each application and requires technical expertise to analyze and enforce policies
Solution Approach 1:
The patent introduces an intermediary layer (semantic data store with ontology) between the diverse business applications and the policy analysis system. This intermediary translates data from multiple applications with different schemas into a unified semantic representation, allowing policy makers to define and analyze policies without needing to learn application-specific terminology or technical details of each data source
2Reliability
If policy analysis requires expertise in specific application terminologies and technical designs, then accurate policy enforcement can be achieved, but it becomes impractical for policy makers without technical knowledge to monitor and control activities
Solution Approach 1:
The semantic data store acts as an intermediary that preserves the accuracy needed for policy enforcement while shielding policy makers from technical complexity. The ontology provides a standardized semantic layer that maintains data accuracy and relationships while presenting a unified, technology-agnostic interface for policy definition and analysis
Solution Approach 2:
The system segments the complex technical infrastructure into distinct layers: the application layer with diverse schemas, the semantic data store layer with unified ontology, and the policy analysis layer. This segmentation allows each layer to operate independently, with the semantic layer translating between technical implementations and policy requirements, making the system accessible to non-technical policy makers while maintaining enforcement accuracy
Data Source
AI summary
Techniques for implementing policies. In an embodiment, first data is stored in a first data store according to a first schema. A second schema is defined based at least in part on a policy and an ontology. Second data, which includes at least a portion of the first data, is stored in a second data store according to the second schema. Storing the second data is based at least in part on a mapping of the first schema to the second schema. At least a portion of the second data is analyzed and results of the analysis are provided to a user.