Distributed Hypergraph Framework for Secure Data Integration

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Solution Overview

Problem

Current data sharing and analytics systems face challenges in integrating diverse data sources across different standards, models, security protocols, and infrastructure, leading to logistical complexities, increased security risks, and privacy concerns, which hinder effective global-scale data sharing and analysis.

Innovation Solution

A distributed hypergraph framework that transforms heterogeneous data sources into a unified knowledge representation, enabling secure, real-time scientific analysis by using a knowledge overlay structure with hypergraph elements and a hypergraph communication protocol, minimizing data replication and movement while ensuring robust security and privacy.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If data from multiple heterogeneous data sources is integrated into a centralized knowledge space, then data sharing and analysis capabilities are improved, but system complexity, security risks, and operational burden increase significantly

Engineering Contradiction:

Improvedata sharing capabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent divides the centralized knowledge space into multiple distributed knowledge spaces, each managed by different organizations. These distributed spaces are connected through a federated architecture that allows data sharing without centralization, thereby reducing system complexity while maintaining adaptability.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces a standardized interface layer and common data models as intermediaries between heterogeneous data sources. This intermediary layer enables seamless integration and sharing across distributed systems without requiring direct connections between all data sources, reducing operational burden and complexity.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If a centralized knowledge space is replicated across multiple sites for backup and availability, then system reliability is improved, but data movement, synchronization complexity, and storage requirements increase

Engineering Contradiction:

Improvesystem availabilityVSAvoiddata movement

Core Design Contradiction:

ReliabilityVSLoss of substance

Solution Approach 1:

The patent allows each distributed knowledge space to maintain local copies of data relevant to its domain while using standardized interfaces to access data from other distributed spaces. This local quality approach ensures high availability without requiring complete replication across all sites, reducing data movement and storage requirements.

Inventive Principle:

Principle #3Local quality

3Productivity

If diverse analytic tools and platforms are coordinated to work together, then analytical capability is improved, but integration complexity and coordination overhead increase

Engineering Contradiction:

Improveanalytical capabilityVSAvoidintegration complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent develops universal data models and standardized interfaces that can be used across multiple analytic tools and platforms. This universality allows diverse analytical tools to work together without complex point-to-point integrations, reducing integration complexity while maintaining high analytical capability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Adaptability or versatility

If data is shared across organizational boundaries with different security protocols, then collaboration capability is improved, but security risks and privacy concerns increase

Engineering Contradiction:

Improvecollaboration capabilityVSAvoidsecurity risk

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The patent establishes standardized security protocols and data governance frameworks in advance before data sharing occurs. These preliminary actions include defining access control policies, data classification schemes, and security requirements that are embedded into the distributed architecture, enabling secure collaboration without ad-hoc security negotiations.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11226945B2Process and framework for facilitating information sharing using a distributed hypergraph

Publication Date: 2022.01.18 GEORGETOWN UNIV

AI summary

A knowledge model “overlay” for organizing and analyzing large, dynamic data volumes is implemented as a hypergraph that manifests as a result of a distributed theory-driven data source transformation process. This process maps exponentially growing data into an asymptotically limited information space. Within this space, real-world entities (e.g. people, computers, cities, Earth) and their complex interdependencies (e.g. social networks, connectivity, causal relationships) are represented as attributed hypergraph elements (i.e. both hypervertices and hyperedges). Attributes are represented as state vectors affixed to any hypergraph element. Transformation of source system data into this overlay structure is accomplished with minimal data movement and replication using a universal “pointer” like mechanism that is managed in a decentralized fashion by the respective transformation components. Access to the knowledge overlay is performed via a hypergraph communication protocol encapsulated within a common hypergraph API and accompanying hypergraph toolkit.