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A Data Engineering Framework for Ethereum Beacon Chain Rewards: From Data Collection to Decentralization Metrics.

Tao Yan1, Shengnan Li1, Benjamin Kraner1

  • 1Blockchain & Distributed Ledger Technologies Group at Department of Informatics and UZH Blockchain Center, University of Zurich, 8050, Zurich, Switzerland.

Scientific Data
|March 29, 2025
PubMed
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This summary is machine-generated.

This study introduces a dataset of Ethereum validator rewards to analyze Proof-of-Stake incentive structures and decentralization. The data enables researchers to evaluate validator behavior and enhance blockchain efficiency and security.

Area of Science:

  • Computer Science
  • Cryptography
  • Economics

Background:

  • Ethereum utilizes a Proof-of-Stake (PoS) consensus mechanism for network security and validator incentives.
  • Challenges in analyzing and optimizing decentralization persist within blockchain technology.
  • Existing data on validator rewards is fragmented, hindering comprehensive analysis.

Purpose of the Study:

  • To introduce a comprehensive dataset of Ethereum validator rewards (attestation, proposer, sync committee).
  • To address data fragmentation and enable robust evaluations of PoS incentive structures.
  • To facilitate research on enhancing blockchain decentralization, security, and efficiency.

Main Methods:

  • Collected and categorized granular validator reward data from the Ethereum Beacon chain.

Related Experiment Videos

  • Applied decentralization metrics including Shannon entropy, Gini Index, Nakamoto Coefficient, and Herfindahl-Hirschman Index (HHI).
  • Developed open-source analytical tools for data utilization.

    • Main Results:

    • A transparent and auditable dataset of validator activities is now available.
    • Demonstrated the dataset's utility in assessing incentive structures and decentralization trends.
    • Established a foundation for analyzing enforceable rules and protocol compliance.

    Conclusions:

    • The dataset provides crucial resources for researchers studying blockchain systems.
    • Enhanced analysis of PoS incentive mechanisms and validator behavior is now possible.
    • Facilitates future research towards more decentralized, secure, and efficient blockchain networks.