Problem: the data interoperability challenge in web3

Blockchains store each account’s state transitions chronologically and permanently. When developers retrieve information surrounding an account, they would be forced to first search for the raw data block by block, transaction by transaction using Remote Procedure Call (RPC) services, further computations can then be carried out to uncover insights. If the account happens to have footprints on multiple blockchains, developers then have to do the same thing for each of the blockchains before proceeding with the final computations.

These “account-centric” use cases are mainly regarding retrieving social relationships of trust or credentials [2] surrounding individual accounts. The credentials are vital yet complex networks of building blocks for a web3 internet. Imagine a scenario where Defi protocols like Uniswap simply want to “recognize” its loyal users and reward them according to their liquidity contributions, a feature almost any web2 application has by default; yet there's no good way for its smart contracts to instantly access any given account’s transaction statistics in a trustless way, i.e. total transaction volume etc. Similarly, wallet applications like MetaMask need to display asset portfolios properly to provide a better user experience, an essential feature any web2 financial applications would support; yet adding support for hundreds of public chains and an ever-increasing number of assets and protocols is no trivial task. Web3 social applications like instant-messaging apps and Linkedin-like applications also need on-chain credentials to help build up trust amongst users. For example, a user with top tier NFTs and a handful of mutual on-chain friends adds a tremendous amount of trust in social settings.

Albeit its importance, large on-chain data usage at scale is becoming exponentially more expensive when compounded by the multi-blockchain ecosystem, in particular with Ethereum’s modular blockchains and upcoming Danksharding [3]. Without a clear solution for the problems, web3 applications struggle to attract the mass consumer market, because it is challenging for them to deliver experiences beyond their web2 counterparts without leveraging the network of data formed by numerous web3 protocols, which will become the driving force that propels web3 applications’ mass adoption. The aforementioned problems can be attributed to a single unfilled gap in the web3 ecosystem – lack of data interoperability layer that bridges application developers and the underneath protocol layer. Such a layer should be designed and built like a utility provider, much like power plants providing electricity which powered industrial revolution, providing utility to power the data & AI democratization in web3 revolution.

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