Context-Rich Key Framework for Interoperable Concept Management
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Solution Overview
Problem
Existing electronic information management systems face limitations in interoperability, scalability, and extensibility due to their reliance on platform- or computer-specific programming, requiring substantial human intervention for communicating equivalence and meaning between systems or digital cultures.
Innovation Solution
The Context-Rich Key (CRK) Framework enables interoperability by defining digital concept managers that encapsulate capabilities and services, allowing for the creation of digital membranes that interact with human and computer systems in a way that models human conceptual understandings, using rigorous semantic definitions to represent user intent and translate it into system-specific expressions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If platform- or computer-specific programming is used to automate electronic behavior, then automation extent is improved, but interoperability between different systems deteriorates
Solution Approach 1:
The patent introduces a universal intermediary layer (global information architecture, translation services, standardized protocols) that mediates between platform-specific systems. This intermediary enables automated interactions while maintaining interoperability by translating between different system languages and formats without requiring direct platform-specific programming between systems.
Solution Approach 2:
The patent creates universal interfaces and standardized data models that can serve multiple platforms and systems simultaneously. By designing system components with multi-functionality that work across different platforms, the solution maintains automation benefits while achieving broad interoperability without platform-specific customization.
2Manufacturing precision
If manual data routing and platform-specific coding are used to represent Computer Artifacts, then manufacturing precision of data representation is improved, but device complexity and human intervention requirements worsen
Solution Approach 1:
The patent creates standardized digital representations (copies) of real-world concepts and data artifacts that can be universally exchanged between systems. These standardized copies maintain the precision needed for accurate data representation while eliminating the need for complex platform-specific coding and manual routing, as the standardized format can be processed automatically across different systems.
3Measurement precision
If substantial human intervention is used for communicating equivalence and meaning between systems, then measurement precision of data meaning is improved, but productivity deteriorates
Solution Approach 1:
The patent implements self-service mechanisms where systems automatically negotiate and translate data meanings using standardized protocols and ontologies. The systems perform their own data validation, format conversion, and semantic alignment without requiring human intervention, thereby maintaining precision in data meaning interpretation while dramatically improving interaction productivity and speed.
Data Source
AI summary
Various implementations provide a Context-Rich Key (“CRK”) Framework for managing computing, networking, concepts, and context from human and system-of-systems perspectives. The CRK Framework provides an environment for defining and implementing interoperability models for collections of distributed applications and/or systems within a digital culture, and for managing concepts between digital cultures. In some implementations, a digital processing system receives a global request, e.g. for information related to a target concept. In some implementations, if the digital processing system has access to data relevant to the target concept, the digital processing system identifies an appropriate local object. In some implementations, the digital processing system then processes the global request to generate and initiate or run a local action. Upon initiation of the local action, local action results are generated. In some implementations, the digital processing system processes the local action results, returns the local action results to the requesting system, or both.