Cloud Data Sharing Connector with Rule Engine
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Solution Overview
Problem
Existing data sharing technologies face challenges in providing controlled, real-time data access among entities, often resulting in complexity, high costs, and loss of data security, especially when dealing with time-sensitive information.
Innovation Solution
A cloud-based connector system that includes business capability modules, a core services module for storing sharing rules, and a capability service module to manage and restrict data access according to predefined rules, allowing contributors to control what data is shared with whom and when, while maintaining data security and scalability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data sharing methods are used to enable real-time data access among multiple entities, then data accessibility and sharing speed are improved, but data security control and access management become compromised
Solution Approach 1:
The patent introduces a data sharing platform as an intermediary system between data providers and data consumers. This platform implements a rule engine that automatically evaluates data access requests against predefined sharing rules, policies, and criteria. The intermediary architecture enables real-time data sharing while maintaining security control, as the platform mediates all access requests and enforces authorization rules without requiring direct peer-to-peer connections between entities.
Solution Approach 2:
The system requires preliminary configuration of data sharing rules, access policies, and authorization criteria before actual data sharing occurs. Data providers pre-define sharing conditions, access levels, and security parameters through the user interface. These preliminary actions establish the framework for automated rule evaluation, enabling fast real-time data access while maintaining pre-established security controls and authorization mechanisms.
2Reliability
If granular access control rules are implemented to control what data is shared with whom, then data security and access control are improved, but system complexity and configuration effort increase
Solution Approach 1:
The patent implements a user-friendly graphical interface that enables data providers to self-configure data sharing rules without requiring complex technical knowledge. The interface presents simplified forms and templates for defining sharing policies, access levels, and authorization criteria. The system automatically processes these user-defined parameters and translates them into executable rules in the rule engine, reducing configuration complexity while maintaining granular access control capabilities.
Solution Approach 2:
The data sharing platform provides universal rule templates and standardized configuration options that can be applied across multiple data types and sharing scenarios. The system supports various sharing models (one-to-one, one-to-many, many-to-many) through a unified rule engine that evaluates requests against configurable parameters. This multi-functionality reduces configuration complexity by providing reusable templates and standardized processes that work across different use cases.
3Adaptability or versatility
If a centralized data sharing platform is deployed to manage data exchange among multiple contributors and consumers, then data sharing control and security are improved, but infrastructure costs and deployment complexity increase
Solution Approach 1:
The patent describes a modular platform architecture where the data sharing system is divided into distinct functional components: data ingestion modules, rule engine, authorization service, data delivery mechanisms, and user interface. Each module can be independently configured, deployed, and scaled. This segmentation allows organizations to deploy only the necessary components for their specific use case, reducing infrastructure costs and deployment complexity while maintaining comprehensive data sharing control capabilities.
Data Source
AI summary
Illustrative embodiments disclose systems for sharing, among a group of consumers, data provided by a contributor. Some embodiments are well-suited for real-time distribution of data developing from ongoing incidents, and may be useful, for example, for emergency management. Illustrative embodiments provide a cloud-based system having tenants that are data contributors and data consumers. The system receives, from each contributor, both data and sharing rules that dictate whether and how that data may be shared, and with whom (which consumer or consumers), and then provide data to such consumer or consumers according to the sharing rules.