Decoupled Cryptotoken Minting for Biological Data
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Solution Overview
Problem
Current blockchain-based cryptographically generated data systems face challenges such as high energy consumption, limited accessibility for new users, and volatility due to their consensus mechanisms, particularly in Proof of Work systems, and incentivize hoarding, leading to deflationary pressures.
Innovation Solution
Decoupling the minting mechanism of cryptotokens from the consensus mechanism by linking them to biological datasets, where contributors receive tokens based on the quality and value of their contributions, such as genetic sequences, to promote accessibility and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Proof of Work consensus mechanism is used, then security and decentralization are improved, but energy consumption increases and accessibility for new users deteriorates
Solution Approach 1:
The patent segments the token issuance process from the consensus mechanism. Token minting is decoupled from block validation, allowing Proof of Authority or other low-energy consensus mechanisms to be used while still providing security through the distributed verification of contribution claims across the network.
Solution Approach 2:
The patent introduces contribution claims and quality certifications as intermediary mechanisms. Instead of directly linking token issuance to computational work, the system uses verifiable contribution records and quality assessments as intermediaries to determine token allocation, reducing the need for energy-intensive proof-of-work while maintaining security through transparent verification.
2Reliability
If Proof of Work mining hardware is required, then security is improved, but ease of operation deteriorates for new users
Solution Approach 1:
The patent enables users to self-verify their contribution claims through the distributed ledger. Each user can independently validate their own contribution records and quality certifications stored on the blockchain, eliminating the need for centralized authorities or complex mining hardware while maintaining security through cryptographic verification.
Solution Approach 2:
The patent uses cryptographic copies of contribution evidence stored on the distributed ledger. Instead of requiring users to possess expensive mining hardware, the system provides verifiable copies of contribution records that can be independently validated by any network participant, greatly improving accessibility while maintaining security through distributed verification.
3Reliability
If token supply is fixed with cap, then scarcity and value are improved, but volatility increases and hoarding is incentivized
Solution Approach 1:
The patent implements a dynamic token supply mechanism where new tokens are continuously minted based on verified biological data contributions. This dynamic issuance model replaces fixed supply caps, allowing the token economy to adapt to actual network participation and data contribution levels, thereby reducing volatility and discouraging hoarding by providing ongoing incentives for active contribution.
Solution Approach 2:
The patent establishes a feedback loop where token issuance is directly tied to verified contributions. Quality certifications and contribution claims create a feedback mechanism that adjusts token supply according to actual network value creation, preventing both excessive hoarding and deflationary pressure while maintaining stable token value through balanced issuance.
4Manufacturing precision
If quality certification is implemented, then manufacturing precision of token value is improved, but device complexity increases
Solution Approach 1:
The patent extracts the quality assessment function from the core consensus mechanism. Quality certification is performed by specialized validators or oracles that operate independently from the main blockchain consensus, allowing complex quality evaluation logic to be separated from the fundamental token issuance and validation processes, thereby managing system complexity while maintaining precision.
Data Source
AI summary
Methods are provided for minting and distributing quantities of cryptographically generated data based on the quality of received biological datasets. Computer readable media, computing apparatuses, and systems are also provided.