Decentralized Data Contexts for Trustless Network Management
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Solution Overview
Problem
Current distributed ledger technologies (DLT) lack effective decentralization in creating and sharing data, particularly for untrusted smart contracts, which hinders reliable data management and attestation processes.
Innovation Solution
A decentralized ecosystem is established through an attestation registry with linked registries for data management, including a property registry, source registry, and attestation registry, enabling flexible data schema definition, access control, and data provenance tracking, allowing authorized users to create, update, and delete data while ensuring data integrity and attribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional centralized data management is used on DLT, then data control and authority are concentrated, but decentralization and trustless operation are compromised
Solution Approach 1:
The patent segments data management into distinct components: data contexts define scopes, sources represent data providers, and properties represent data elements. This segmentation allows decentralized authorization where each component can be independently managed and authorized, resolving the contradiction between reliability and decentralization complexity.
Solution Approach 2:
The patent introduces an attestation registry as an intermediary layer between data sources and consumers. This registry stores and verifies attestations (authorization proofs) without requiring direct trust between parties, enabling trustless decentralized data management while maintaining reliability through cryptographic verification.
2Reliability
If oracles are used for data verification, then data authentication is improved, but centralization of trust and single points of failure are introduced
Solution Approach 1:
The patent enables data sources to self-attest their own data through cryptographic signatures and decentralized identification. Instead of relying on external oracles to verify data, the system allows data providers to autonomously sign and attach attestations to their data, eliminating single points of failure while maintaining authentication reliability.
Solution Approach 2:
The attestation registry serves multiple functions: storing attestations, verifying signatures, tracking data provenance, and enabling cross-context data sharing. This universal mechanism replaces multiple specialized oracle services with a single decentralized infrastructure that handles authentication, authorization, and data management across diverse applications.
3Adaptability or versatility
If flexible data schemas are implemented, then adaptability to different data formats is improved, but data management complexity and access control difficulty increase
Solution Approach 1:
The patent applies local quality by allowing each data context to have its own schema definitions and validation rules tailored to specific data types and requirements. Different contexts can define custom properties, data formats, and validation logic without imposing complexity on the entire system, as each context's schema is locally optimized for its specific purpose.
4Reliability
If data access control is enforced, then data security and authorization are improved, but data sharing and consumption are restricted
Solution Approach 1:
The patent implements preliminary action by requiring data sources to pre-generate and attach attestations (authorization proofs) to their data before sharing. This preliminary authorization allows data to be shared widely without real-time access control checks, as the authorization is embedded in the data itself through cryptographic signatures, improving sharing efficiency while maintaining security.
Data Source
AI summary
A framework for managing data on a decentralized network is disclosed. The framework is designed to manage two conflicting forces, openness and control, in order to provide scalable trust on trustless networks. To manage this conflict, a flexible, decentralized governance model is disclosed to enable any DLT user to create and manage data contexts, a virtual boundary for controlling data rights, meaning, and value so as to produce accountable, trusted data with full provenance. The framework does not need to determine who should be trusted, how the trust network forms, or how meaning is developed while providing a governance model by which any authorized user can contribute meaning (properties) and monetize attributable data (attestations).