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Grassroot DataDAOs

Grassroots dataDAOs let users contribute data to communal pools, minting tokens ($GdD) based on data quality and staked $CRC. Users pay for AI services with these tokens. Organizations buy tokens to access data, driving token value and rewarding contributors.

Grassroot DataDAOs

Created At

ETHGlobal Bangkok

Winner of

Gnosis - Build social and community focused dApps using Circles SDK 1st place

Project Description

Grassroots dataDAOs empower users to contribute their data to communal pools, minting group tokens ($GdD) proportional to the quality of their data and staked $CRC tokens. Users leverage these tokens to access AI services like privacy-preserving matchmaking—paying with their data, not their privacy. Organizations and other data consumers cannot join the dataDAO directly; they must purchase $GdD tokens from the market to access the data pool. A minimum price per data consumption is enforced, preventing dataDAO members from consuming more than personal demand with initial $GdD minted. Consumer demand drives the token's value, incentivizing data contributions and liquidity provision in AMM pools. Revenue generated from computations on the dataDAO vault accumulates in a shared pool, allowing data owners to share profits through models governed by the dataDAO community.

How it's Made

We developed a custom minting policy on the group contract that allows users who have contributed data to mint group tokens ($GdD). The amount of tokens minted is proportional to the quality of their data, measured by summing the confidence scores of the triplets extracted from their raw data. This approach ensures that users are fairly rewarded based on the value they add to the communal data pool.

Looking ahead, the plan is to store the data pool within a Trusted Execution Environment (TEE). This will enable computations to be performed without revealing users' personal data. Users' consent for different use cases will be attached directly to their data triplets, allowing computation jobs to identify suitable data sets via SPARQL queries while respecting user permissions.

To protect the anonymity of dataDAO members, SPARQL queries will be restricted from targeting groups smaller than 100 members when applying filters. Additionally, an internal committee within the dataDAO will be established to authorize computation jobs initially. This governance mechanism will help prevent misuse and ensure that all computations align with the community's privacy standards.

By combining a fair token minting policy with robust privacy protections and community governance, the system aims to empower users to contribute and monetize their data securely while enabling valuable AI services.

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