Orange protocol
Orange is a reputation and trust minting protocol that aggregates data and Web3 reputation models to generate comprehensive reputation proofs in the form of Verifiable Credentials and NFTs.
Verifiable credentials basically contain information that is necessary to determine if the credential is genuine. Any party can issue credentials in a trust network. That would make them a source of trust within the network. Users store and maintain credentials after they’re issued. They may choose to selectively, or totally share the data within a credential with credential consumers, who then verify it using the attested record on a public ledger such or Ethereum.
It can be used to objectively calculate and assess the "reputation" for a Decentralized Identifier (DID), and associated wallet addresses.
Decentralized identifiers (DIDs) are a new type of identifier that enables verifiable, decentralized digital identity. A DID refers to any subject (e.g., a person, organization, thing, data model, abstract entity, etc.) as determined by the controller of the DID.
It takes multiple data points into account to assess user behaviour and preferences, such as:
OnChain data
- Transaction data indicating user behavior
- Balance and ownership history of assets (exchangeable tokens, NFTs, social tokens, etc.)
- Interaction with smart contracts
- Historical ownership and transaction data
Off-chain data
- Data from games and other apps, e.g., collectibles, in-app purchases, etc.
- Reviews, ratings from various platforms
- User profile information from social media and other platforms
- IoT data such as locations, health data, etc.
- Financial data from institutions like banks, insurance companies, etc.
- KYC verification through government-issued IDs such as driving license, or proof of university qualification, etc.
The Orange system receives call requests from applications with specific models and datasets.
It first invokes the model specified in the call request by sending the request to a service created by the model provider (MP).
Then, based on the selected data provider (DP) and dataset, the system retrieves the data using the interface provided by it. Once the computation is completed and the result is retrieved, the system temporarily stores it until it is retrieved by the application.
The system processes model call requests in the form of tasks. Each task corresponds to an individual decentralized identifier (DID) or wallet address.
The application can then receive the result in raw form (data object) or send a request to export it as a verifiable credential or NFT.
The following figure shows how the different components that make up the Orange system are connected and interact with each other.
Orange supports user-generated reputation evidence in the form of verifiable credentials (VCs) and NFTs. VCs are generated based on a user-selected pair of dataset and model and contain a reputation score. Users whose reputation exceeds relevant thresholds can claim NFTs so that their reputation can be used in more scenarios.
Orange provides 3 NFTs, Crypto Whale, NFT Collector and Web3 Citizen, which evaluate a user's reputation using different standards.
For example, NFT Collector is built from datasets and a model aimed at evaluating active NFT users based on their asset ownership and related actions:
Datasets:
- The timestamp of the first transaction of an NFT user
- Number of transactions on OpenSea within 180 days
- Types of ERC721 and BEP721 owned by NFTs
- The value of ERC721 and BEP721 owned NFTs
However, these models are for general purposes. Application owners are encouraged to provide data and models to Orange and release custom NFTs so that the reputational results generated are more relevant to their needs.
Use cases
Communities and dApps can release reputation-based NFTs with different user reputation requirements to provide users with utilities to which certain NFT owners are entitled.
Granting Entry. A user's entry into a system can be designed based on criteria such as:
- Sybil-resistant identity verification
- Possession of particular fungible or NFT assets
- Social-media verification
- Subscriber count and endorsements, and etc.
User participation, involvement and contribution
- Initiating and discussing proposals
- Participation in voting
- Contribution to treasury management, etc.
- Records of donations to public goods
- Records of participation in certain activities
Reputation and influence on decision making
- past decision results
- proven expertise
- proven credibility with other community members
A user's creditworthiness to receive certain levels of service can be established based on data such as:
- transaction history
- asset attributes
- verified off-chain financial risk data
- verified identities
