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A Blockchain-Based Architecture for Trust in Collaborative Scientific Experimentation.

Raiane Coelho1, Regina Braga1, José Maria N David1

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Summary
This summary is machine-generated.

This study introduces BlockFlow, a blockchain-based architecture enhancing trust and traceability in scientific collaboration. It ensures data integrity and reproducibility for shared research, like genomic sequencing.

Keywords:
BlockchainCloud computingCollaborative scientific experimentsCoronavirusGenomic sequencingProvenanceReproducibility

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Data Science

Background:

  • Scientific collaboration relies on data sharing, idea exchange, and result dissemination for knowledge advancement.
  • Ensuring interoperability, privacy, traceability, and trust is crucial for effective scientific collaboration.
  • Provenance is vital for tracking experimental steps, supporting reproducibility and scientific integrity.

Purpose of the Study:

  • To propose and evaluate BlockFlow, a novel architecture integrating blockchain, provenance, and cloud infrastructure.
  • To enhance trust and traceability in collaborative scientific experiments through a secure and transparent framework.
  • To address data heterogeneity and facilitate interpretation for geographically distributed researchers.

Main Methods:

  • Developed the BlockFlow architecture utilizing blockchain technology (Hyperledger) and provenance tracking.
  • Implemented a scenario involving genomic sequencing of SARS-CoV-2 to demonstrate the architecture's capabilities.
  • Focused on ensuring data sharing, interoperability, and secure execution of collaborative experiments.

Main Results:

  • The BlockFlow architecture successfully demonstrated enhanced trust and traceability in collaborative scientific experimentation.
  • The system effectively managed data heterogeneity, aiding interpretation by distributed researchers.
  • The blockchain-based approach reinforced transparency and data integrity throughout the experimental workflow.

Conclusions:

  • BlockFlow provides a robust solution for secure and transparent collaborative scientific research.
  • The integration of blockchain and provenance significantly improves data sharing, traceability, and trust.
  • This architecture supports the reproducibility and reliability of scientific findings in a collaborative environment.