Inspiration
With the development of Web3, a variety of NFT types are used based on different scenarios.Therefore, the data is scattered everywhere.The Cluster3 team found that if the scattered data can be integrated and made into dynamic NFT representing user portraits, it will be a huge treasure.
What it does
We integrate on-chain data credentials and off-chain behavior data(e.g. POAP/OATs, ERC-20 token,Voting data, behavioral label data, etc.）,and build a comprehensive user profile, to present externally in the form of dynamic NFT, so that the project party can intuitively understand the users, allowing users to trace back their contributions.
How we built it
Chainlink AnyAPI:We issued a dynamic NFT on polygon, in which the RankURL attribute is added to the outer attribute of the NFT. This attribute can transmit the ranking data calculated by cluster3 to the contract of the dynamic NFT through the Any API function of ChainLink.
Dynamic NFT image:For the dynamic NFT display effect, we specially designed treasure chest images for different levels of users. According to the user's contribution ranking, users will see different styles of treasure chests, and different styles of treasure chests also have different animation effects.
Challenges we ran into
Gas fee limit: After obtaining user information, we calculate and organize to form a contribution score and ranking, and update these data to the user's dynamic nft contract, which is a huge consumption of gas fee.We solve this problem by reducing the user's data update frequency and single-point update. First, update all user data at a fixed time every day, and secondly, use a single-point update method to detect that a fixed user has new data and then update user data.
**Complexity of the contract: **The user data in Cluster3 dynamic NFT includes the user's on-chain and off-chain data. The combination of smart contracts and off-chain data will greatly increase the complexity of the contract. The Chain Any API helped us a lot to solve this problem.
Accomplishments that we're proud of
Cluster3 has now covered 1200+ communities, collated and calculated the data credentials of 1.2 million user addresses and helped these users calculate their contribution score and ranking to each community.
What's next for Cluster3
- Enrich the user portrait data of cluster3, consider introducing more user data certificates to enrich the user image, and make our contribution score more accurate.
- Establish a community achievement system based on users' on-chain and off-chain behavioral data credentials.
- Sort user Data Credentials,and based on the calculated user's contribution score in the community, and produce more user analysis models for different project parties.
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