DeFiGraph – Knowledge Graph (KG) for DeFi
The proposal outlines the need for a DeFi Knowledge Graph (KG) to simplify and democratize access to decentralized finance (DeFi) data. It highlights the complexity of DeFi and the lack of user-friendly interfaces, making it difficult for users and developers to engage effectively. The project, called DeFiGraph, aims to create a KG that maps relationships between various DeFi entities, backed by Language Learning Models (LLMs) for natural language queries.
Key components include data collection, KG design, semantic mapping, graph database implementation, and an interactive user interface. The project's innovation lies in combining a KG with a user-friendly interface. It envisions a range of applications, from personalized DeFi bots to on-chain yield products and real-time credit scoring systems.
Stakeholders include L3A, Openmesh, MIT, and Neo4j consultants. The estimated budget is $40,000, allocated mainly to external consultants. Success metrics include milestone completion, data quality, user engagement, technical accuracy, and industry impact.
Milestone 1 focuses on data gathering, preprocessing, and infrastructure setup, involving data source identification, API integration, data normalization, and xNode deployment. Milestone 2 covers KG and model development over ten weeks.