IRC-Infoid Data Standardization for Cross-Platform Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data archival systems lack a unifying standard for cross-platform communication and data transfer, leading to high costs and complexity in capturing, processing, and using data, which limits its usability and requires expert guidance, stifling growth and accessibility.
Innovation Solution
An object-oriented data management system utilizing an IRC-Infoid Engine that creates and manages standardized IRC-Infoid data structures, enabling efficient data transfer and use across disparate systems through properties like event, user, file, message, and relationship, with an IRC-Infoid Runner for API endpoints and authentication, and a structural standardization module for integrity and conformity checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a unifying data standard is implemented across multiple systems, then data transfer efficiency and accessibility improve, but system complexity and implementation costs increase
Solution Approach 1:
The patent creates a universal data standard (IRC-Infoid) that can be applied across multiple disparate systems and platforms. The standardized data structure with defined properties (event, user, file, message, data, relationship) serves as a multi-functional framework that enables different systems to communicate using a common language, thereby improving data transfer efficiency without requiring complete system redesign
Solution Approach 2:
The patent transforms unstandardized data from various sources into a standardized format by changing key parameters including data structure organization, property definitions, and relationship representations. This parameter transformation allows existing data to be converted into the IRC-Infoid standard through processing rules and validation mechanisms, balancing standardization benefits with implementation feasibility
2Reliability
If expert guidance is required for each data implementation, then data integrity and security are maintained, but accessibility and growth potential are limited
Solution Approach 1:
The standardized IRC-Infoid framework enables systems to autonomously process and validate data according to predefined rules without requiring constant expert intervention. The built-in validation mechanisms, processing rules, and standardized structure allow systems to self-verify data integrity, while the common framework makes data accessible to users without expert guidance
Solution Approach 2:
The patent introduces an intermediary layer (the standardized data framework and processing engine) that mediates between raw data sources and end users. This intermediary automatically handles data validation, transformation, and security checks, maintaining data integrity while presenting accessible, standardized data to users without requiring them to understand complex underlying systems
3Adaptability or versatility
If data is stored in disparate formats across systems, then system independence and flexibility are maintained, but data search and retrieval efficiency decrease
Solution Approach 1:
The patent segments data into standardized components with defined properties (event, user, file, message, data, relationship) that can be independently processed and searched. This segmentation allows systems to maintain independence while enabling efficient search operations by indexing and querying specific property segments rather than searching through unstructured disparate formats
Data Source
AI summary
An object-oriented data management method and system comprising nested structural-elements that form inter-related containers of IRC-Infoids that include information, processing-rules, and an atomic-action layer, enabling functions to operate across disparate-systems using self-normalizing data-definitions is disclosed. The creation and management of the IRC-Infoid objects, rules and actions are handled by an IRC-Infoid Engine. The IRC-Infoid is an object with its own definitions, properties, and rules, related to a single parent element. Six properties define the IRC-Infoid: event, user, file, message, data and relationship. These properties follow inter-relationship rules, which force internal consistency, data optimization, and maintain data integrity. The IRC-Infoid data structure includes documentation, thought leadership and chatter, which when parsed through the rule sets, gets attached to standard or triggered actions, including periodic updates and called actions for use across disparate systems.