Blockchain Data Blocks with Dynamic Graph Models

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Solution Overview

Problem

Conventional blockchains face challenges in efficiently managing and analyzing data due to their fixed block structure and data fields, which restricts their ability to perform complex queries, machine learning, and artificial intelligence tasks while compromising data immutability and security.

Innovation Solution

A computational architecture that treats data blocks as dynamically configurable smart data objects, allowing each block to vary in fields, schemas, and size, and employs graph models and machine learning to learn and represent relationships between data stored across different blocks, enabling consent-based sharing and enhanced data management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional blockchains use fixed block structure and fixed data fields, then data security and immutability are maintained, but the ability to perform complex queries, machine learning, and analytics is restricted

Engineering Contradiction:

Improvedata security and immutabilityVSAvoidability to perform complex queries, machine learning, and analytics

Core Design Contradiction:

ReliabilityVSAdaptability or versatility

Solution Approach 1:

The patent implements dynamically configurable block structures where fields, schemas, and block sizes can vary based on computational requirements. This allows the blockchain to adapt its structure for different analytical tasks while maintaining cryptographic security through hash linking, thus resolving the contradiction between fixed structure for security and dynamic structure for analytical versatility.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes key parameters of block structures including field types, schema configurations, and block sizes to optimize for different computational tasks. By allowing parameter variation in block definitions while preserving the immutable hash chain, the system enables complex queries and machine learning operations without compromising data security.

Inventive Principle:

Principle #35Parameter changes

2Ease of manufacture

If data is stored in non-optimized or indexed flat files in conventional blockchains, then storage simplicity is maintained, but searching and data gathering efficiency deteriorates

Engineering Contradiction:

Improvestorage simplicityVSAvoidsearching and data gathering efficiency

Core Design Contradiction:

Ease of manufactureVSProductivity

Solution Approach 1:

The patent implements preliminary indexing and optimization of data structures during the block creation and storage phase. By pre-organizing data with efficient indexing mechanisms before queries are executed, the system enables fast searching and data gathering operations while maintaining the simplicity of flat file storage architecture.

Inventive Principle:

Principle #10Preliminary action

3Reliability

If a two-step data gathering and validating process is used in conventional blockchains, then data security is maintained, but operational overhead and time requirements increase

Engineering Contradiction:

Improvedata securityVSAvoidoperational overhead and time required

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent merges the data gathering and validation steps into a unified process by implementing validation rules and consensus mechanisms that operate during the single data retrieval operation. This consolidation eliminates the sequential two-step process, reducing operational overhead and time requirements while maintaining cryptographic security through integrated validation.

Inventive Principle:

Principle #5Merging (Combining)

4Adaptability or versatility

If conventional blockchains require separate blockchains for different data types, then data type specificity is maintained, but system complexity and operational overhead multiply

Engineering Contradiction:

Improvedata type specificityVSAvoidsystem complexity and operational overhead

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent implements a universal blockchain architecture with dynamically configurable block structures that can accommodate multiple data types within a single chain. By using flexible schema definitions and field configurations, the system provides multi-functionality that eliminates the need for separate specialized blockchains, thereby reducing system complexity and operational overhead while maintaining data type specificity.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS20250158842A1Graph models of relationships between data stored in blocks on distributed ledgers that are learned through machine learning and platforms for creating, cataloging, and storing the same

Publication Date: 2025.05.15 BURSTIQ INC

AI summary

Introduced here is a computational architecture (also referred to as a “computational infrastructure”) that addresses the limitations of traditional data management solutions using a highly secure data management solution coupled with consent-based sharing. At a high level, the computational architecture applies blockchain methodologies to both transaction data and business data such that both types of data are stored “on chain” in the same computational architecture. This enables several significant advantages over traditional data management solutions with respect to data security, data ownership, data sharing, and intelligence.