From 'Data Islands' to 'Value Sharing': How #Caldera Enables Rollup Data to Generate Compound Interest
The data on the blockchain should be 'shared wealth'—but the reality is that each Rollup's transaction records and user behavior are confined within their own chains, unable to be utilized by other ecosystems, resulting in significant waste. #Caldera (ERA)'s Metalayer is breaking this 'data island' phenomenon, allowing on-chain data to generate a 'compound interest effect'.
Its 'Cross-Chain Data Protocol' functions like a 'decentralized database':
- Data Standardization: Unifying transaction formats and user tags across different Rollups, enabling developers to call 'full ecosystem user profiles' with one click. For instance, if a DeFi project wants to conduct targeted marketing, it can query users who have traded on the NFT chain and have a DeFi chain balance >1000U, resulting in a 3-fold increase in conversion rate;
- Privacy Protection: Data queries only return 'statistical results', without disclosing individual user information. When an analysis agency uses #Caldera data to compile a report, it can calculate the 'average holdings of cross-chain users', but cannot see the asset situation of specific addresses;
- Incentive Contribution: Rollups providing data can earn $ERA rewards, while developers using the data pay ERA, creating a cycle where 'the more data is used, the more valuable it becomes'.
This 'data sharing' has spawned new play styles: a prediction market uses the full ecosystem's transaction data to train AI models, improving the accuracy of rise and fall predictions to 75%; a DAO optimized governance proposal design through analyzing cross-chain voting records, increasing participation from 20% to 50%.
$ERA acts here as 'data currency': data queries, analysis, and sharing are all settled using ERA, and holding $ERA also allows one to vote on 'which data can be shared' and 'how profits are distributed'. @Caldera Official is proving that the value of blockchain lies not only in 'assets' but also in 'the flow and reuse of data'.
