Proof-of-Contribution

This measures contributions to the core protocol's codebase and infrastructure. It includes:

• Code commits and pull requests to the canonical repository.
• Auditing and security reviews of smart contracts.
• Node operation and uptime for networks requiring validators or sequencers.
• Infrastructure provisioning, such as running indexers or RPC endpoints.

Examples: An Ethereum core developer submitting an EIP implementation, or an Avalanche validator maintaining 99.9% uptime.

This quantifies active, informed participation in a protocol's decentralized decision-making processes. Key actions include:

• Voting on proposals with governance tokens or via delegation.
• Submitting well-researched proposals that reach a quorum.
• Participating in governance forums (e.g., Discourse, Commonwealth) with substantive discussion.
• Delegating voting power to reputable delegates.

PoC systems aim to reward quality over quantity, often weighting votes by reputation or the depth of engagement to mitigate low-effort Sybil attacks.

This measures contributions to a protocol's financial depth and stability, crucial for DeFi applications. It tracks:

• Capital deposited into liquidity pools (e.g., Uniswap, Curve).
• Borrowing/lending activity on money markets (e.g., Aave, Compound).
• Providing insurance or coverage in protocols like Nexus Mutual.
• Staking native tokens to secure proof-of-stake networks.

Contributions are often weighted by Total Value Locked (TVL), duration, and associated risk (e.g., impermanent loss) to calculate a contribution score.

This measures contributions that expand the protocol's user base and knowledge base, which are harder to quantify but vital for adoption. It includes:

• Creating high-quality educational content (documentation, tutorials, translations).
• Providing technical support in community channels (Discord, Telegram).
• Organizing or speaking at community events (meetups, conferences).
• Onboarding new users and developers to the ecosystem.

PoC mechanisms often use peer validation or retroactive funding rounds (like Gitcoin Grants) to assess and reward these social contributions.

This measures contributions of reliable external data, which is essential for many blockchain applications' functionality. It involves:

• Operating oracle nodes that feed accurate price data (e.g., Chainlink, Pyth).
• Curating data sets for decentralized knowledge graphs (e.g., The Graph).
• Providing verifiable randomness for applications like gaming and NFTs.
• Submitting and validating real-world events for insurance or prediction markets.

Contributions are scored based on data accuracy, latency, and uptime, with penalties for incorrect or delayed reports.

This measures contributions to a protocol's cultural layer and NFT ecosystem, which drives community identity and engagement. It encompasses:

• Minting or collecting NFTs that define a project's aesthetic.
• Curating galleries or exhibitions within virtual worlds or marketplaces.
• Developing IP and lore that expands the protocol's narrative universe.
• Creating tools for artists and creators within the ecosystem.

While highly subjective, PoC systems can measure these contributions via community voting, secondary sales volume, or usage metrics of created assets.

A core challenge is preventing a single entity from creating many fake identities (Sybil attacks) to claim disproportionate rewards. Mitigation requires robust identity verification or proof-of-uniqueness mechanisms, such as biometrics or trusted attestations, which can conflict with decentralization and privacy goals. Without this, the economic model is vulnerable to manipulation.

Unlike proof-of-work's objective hash rate, the 'value' of a contribution is often subjective and must be quantified. This creates attack vectors:

• Gaming the metrics: Participants optimize for measurable signals (e.g., generating low-quality content) rather than genuine value.
• Oracle reliance: Systems may depend on oracles or committees to score contributions, creating central points of failure or corruption.
• Collusion: Groups can coordinate to inflate each other's contribution scores.

In PoC systems where rewards are distributed via community voting or curation (e.g., for content or grants), collusion is a major threat. Participants can form cartels to:

• Vote for each other's contributions exclusively.
• Engage in bribery or vote-selling outside the protocol. This undermines the meritocratic goal and can lead to centralization of rewards among a coordinated minority.

The tokenomics must be carefully designed to ensure long-term security.

• Hyperinflation: Over-issuance of rewards can devalue the native token, reducing incentive alignment.
• Whale dominance: Early or wealthy contributors can accumulate enough stake to dominate future contribution evaluation, creating a feedback loop.
• Nothing-at-stake: If validating contributions is costless, participants may approve all submissions, degrading system quality.

Contributions (e.g., data sets, compute work) must be stored and made available for verification. Challenges include:

• Data withholding: A contributor may prove they performed work without revealing the output.
• Storage cost: Maintaining contribution history for audit can become prohibitively expensive.
• Fraud proofs: Implementing efficient fraud proofs or zero-knowledge proofs to verify work without re-execution is complex and computationally intensive.

PoC networks often rely on centralized components for practicality, creating single points of failure.

• Contribution oracles: Trusted entities that attest to real-world work.
• Reputation systems: Off-chain scores that influence on-chain rewards.
• Identity providers: Centralized KYC services for Sybil resistance. These dependencies can undermine the censorship-resistance and trustlessness of the system.

The core technical challenge in any PoC system. It refers to the method by which the network cryptographically proves that a participant has performed the useful work they claim. This often involves:

• Zero-Knowledge Proofs (ZKPs) to verify computation without revealing data.
• Trusted Execution Environments (TEEs) for secure, attestable computation.
• Proof-of-Replication for storage contributions. Without robust verification, PoC systems are vulnerable to cheating.

An economic model closely associated with PoC networks. Participants must acquire and often stake the network's native token to earn the right to perform work (e.g., provide a service). They are then paid in that token for completing verified work. This aligns incentives, as token value is tied to demand for the network's services. Livepeer (LPT) for video transcoding is a canonical example of this model in action.

A broad category of protocols that use crypto-economic incentives to build and operate real-world physical infrastructure. PoC is the consensus and reward layer for many DePINs. Examples include:

• Helium (HNT): Rewards for providing wireless network coverage.
• Render Network (RNDR): Rewards for providing GPU rendering power.
• Filecoin (FIL): Rewards for providing decentralized storage. PoC mechanisms determine how contributions to these networks are measured and rewarded.