Why Research Reputation Should Be a Public Good, Not a Private Asset

A researcher's impact is locked in private platforms like Google Scholar, ResearchGate, and university HR systems. This creates massive discovery friction and prevents composable reputation.

• Data Silos: No unified view of a scientist's grants, publications, and peer reviews.
• Vendor Lock-In: Platforms monetize access to reputation data they don't own.
• Inefficient Allocation: Funders can't programmatically identify experts, wasting ~30% of grant admin budgets on search.

Reputation as a public graph of verifiable attestations (VAs) on networks like Ethereum Attestation Service (EAS) or Optimism's AttestationStation. This turns reputation into a composable primitive.

• Sovereign Identity: Researchers own their graph via wallets (e.g., ENS).
• Composable Legos: Protocols like Hypercerts for funding or VitaDAO for review can query the graph programmatically.
• Trust Minimization: On-chain proofs replace institutional letterheads, reducing fraud.

An open reputation layer enables novel coordination mechanisms impossible in closed systems, moving beyond simple scoring.

• Retroactive Funding: Protocols like Optimism's RPGF can use the graph to reward past contributions automatically.
• Delegated Review: Reputation stakes can be delegated for peer review, aligning incentives (see Karma GAP).
• Sybil Resistance: Dense, attested graphs make Gitcoin Passport-style sybil attacks cost-prohibitive for serious science.

Today, research reputation is a private asset locked in silos like VC portfolios and closed analyst networks. This creates massive inefficiency:

• Information Asymmetry: The best insights are gated, not shared.
• Duplicated Work: Every fund rediscovers the same alpha, wasting ~$100M+ in annual analyst hours.
• Centralized Gatekeeping: A few firms control access to quality signals, stifling innovation.

Protocols like Ethereum Attestation Service (EAS) turn subjective reputation into a verifiable, portable public good. Think of it as a decentralized LinkedIn for research quality.

• Sovereign Identity: Analysts own their reputation graph across any app.
• Composable Signals: DApps can query a global graph of attestations for due diligence or curation.
• Sybil Resistance: Leverages Proof-of-Humanity and on-chain activity to filter noise.

Open reputation needs economic security. Builders are using token-curated registries (TCRs) and prediction markets like Polymarket to crowdsource and financially back quality signals.

• Skin-in-the-Game: Stake tokens to vouch for research, aligning incentives.
• Dynamic Pricing: Market odds on a report's accuracy provide a probabilistic truth signal.
• Automated Curation: Protocols like Ocean Protocol can auto-reward high-signal researchers.

These are the front-end aggregators making public reputation usable. Gitcoin Passport aggregates Web2/Web3 identity stamps into a sybil-resistant score. Sismo uses zero-knowledge proofs for selective, private reputation disclosure.

• Aggregated Trust: Combines BrightID, ENS, POAPs into a single score.
• Privacy-Preserving: Prove you're a top-10% researcher without revealing your identity.
• Plug-and-Play: A score that any dApp can integrate in ~5 API calls.

Sustainable public goods need funding. RetroPGF rounds, pioneered by Optimism, demonstrate a model where the ecosystem retroactively pays for high-impact research. This creates a flywheel.

• Output-Based Rewards: Pay for proven impact, not promises.
• Community Curation: Token holders vote on value distribution.
• Positive-Sum: Aligns researcher incentives with long-term protocol health.

The convergence of these protocols enables a user-owned data marketplace. Imagine a terminal where:

• Research is Tokenized: Reports are NFTs with revenue splits.
• Reputation is Liquid: Your score unlocks undercollateralized loans via Arcade.xyz.
• Curation is Automated: DAO treasuries auto-subscribe to researchers based on EAS scores. This dismantles the $50B+ proprietary data oligopoly.

Every protocol—from Aave to Compound—builds its own risk model, leading to fragmented, non-portable user profiles. This creates massive onboarding friction and redundant work.

• Inefficient Capital: Users must rebuild credit from zero on each new chain or app.
• Wasted R&D: Teams spend millions replicating basic KYC/AML and Sybil-resistance checks.
• Market Failure: No single entity can see the full financial graph, crippling underwriting.

Reputation must be a verifiable, composable primitive. Think Ethereum Attestation Service (EAS) or Verax, not a private API.

• Composability: A credit score from Goldfinch can inform a collateral factor on MakerDAO.
• User Sovereignty: Individuals own and permission their data, breaking platform lock-in.
• Auditable Logic: Risk models are transparent, enabling public scrutiny and rapid iteration.

The real asymmetric bet isn't another lending front-end; it's the foundational reputation layer that every DeFi and on-chain social app will query.

• Protocol Moats: Network effects accrue to the standard, like The Graph for indexing.
• Unlocks New Markets: Enables undercollateralized lending, sophisticated DAO governance, and compliant DeFi.
• Regulatory Hedge: A public, auditable reputation system is more defensible than opaque black boxes.

Stop building isolated reputation systems. Integrate with or contribute to open primitives like EAS, Gitcoin Passport, or Orange Protocol.

• Faster GTM: Launch with pre-verified user cohorts in ~1 month, not 12.
• Shared Security: Leverage collective Sybil-attack data from Optimism's RetroPGF rounds or Arbitrum's DAO.
• Cross-Chain Native: Design for users, not silos, using attestation bridges like Hyperlane or LayerZero.