Semantic Policy Composition System for Cross-Application Enforcement
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Solution Overview
Problem
Businesses face challenges in implementing policies due to the need for technical expertise to analyze data across various custom-built applications, which are often incompatible and require specific terminologies, making it impractical for non-technical policy makers to enforce policies across multiple systems.
Innovation Solution
A system and method that uses semantic objects and an intuitive interface to allow users to define policies by arranging objects representing business data, converting these arrangements into executable instructions, and applying data analysis techniques, enabling policy enforcement across diverse applications without requiring deep technical knowledge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data analysis is performed using application-specific languages and technical terminologies, then measurement precision and analysis accuracy are improved, but ease of operation deteriorates as non-technical policy makers cannot create policies
Solution Approach 1:
The patent introduces a semantic layer as an intermediary between the data storage layer and the policy enforcement layer. This semantic layer provides a standardized vocabulary and data model that translates application-specific data into universal business concepts, allowing non-technical users to create policies without needing to understand underlying database schemas or application-specific terminologies while maintaining analysis accuracy
2Adaptability or versatility
If multiple custom-built applications are used to facilitate business activities, then adaptability and business functionality are improved, but device complexity increases making it impractical to manually monitor all activities
Solution Approach 1:
The patent creates a universal data model and semantic framework that can work across multiple different applications and data sources. The standardized schema and ontology allow the same policy enforcement mechanism to operate on data from various applications without requiring application-specific customization, reducing the complexity of monitoring activities across diverse systems
3Measurement precision
If policy makers learn specific application terminologies to create policies, then measurement precision improves, but loss of time increases due to the burden of learning multiple terminologies
Solution Approach 1:
The patent changes the parameter of data representation from application-specific technical schemas to a standardized semantic model with universal business concepts. This parameter change allows policy makers to work with familiar business terminology rather than learning multiple application-specific terminologies, reducing training time while maintaining the precision needed for accurate policy definition through the structured semantic framework
Data Source
AI summary
Embodiments of the present invention relate to techniques for creating policies. A plurality of objects representative of semantic objects are provided to a user. An arrangement of a subset of the objects, the arrangement representative of a policy, is received. The arrangement is converted to instructions for implementation by an application configured to implement policies. One or more of the objects may include fields and/or controls for specifying criteria of semantic objects represented by the objects.