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A decentralized future for the open-science databases.

Gaurav Sharma1, Viorel Munteanu2,3, Nika Mansouri Ghiasi4

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Summary
This summary is machine-generated.

Centralized biological data repositories face risks like cyberattacks and funding issues. A shift to decentralized and federated models enhances data resilience, accessibility, and sustainability for open science.

Keywords:
data accessibilitydata fragmentationdata sharingdatabasefederal governmentfunding instabilityopen-accessscientific data

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Area of Science:

  • Bioinformatics
  • Data Science
  • Scientific Data Management

Background:

  • Centralized biological data repositories are crucial for scientific research but vulnerable to single points of failure (e.g., cyberattacks, funding instability).
  • Disruptions in data access can cause data loss, integrity issues, and significant delays, paralyzing diverse research activities.
  • The increasing volume of data and global uncertainties necessitate re-evaluating the sustainability of centralized models.

Purpose of the Study:

  • To examine the structural limitations of current centralized scientific data repositories.
  • To evaluate the potential of federated and decentralized architectures for enhancing data infrastructure resilience.
  • To propose a hybrid framework for resilient, fair, and sustainable scientific data stewardship.

Main Methods:

  • Analysis of the vulnerabilities inherent in centralized data storage and distribution models.
  • Evaluation of federated (e.g., ELIXIR) and decentralized (e.g., DeSci) approaches to data infrastructure.
  • Development of a hybrid framework integrating existing models for improved data stewardship.

Main Results:

  • Centralized models present significant risks, including data unavailability, loss, and integrity compromise.
  • Federated and decentralized architectures offer enhanced resilience against governance instability, infrastructural fragility, and funding volatility.
  • A hybrid framework can promote equity, global accessibility, and long-term sustainability for scientific data.

Conclusions:

  • A transition towards federated and decentralized data infrastructures is essential for the future of open science.
  • Integrating complementary approaches can create a globally distributed, economically sustainable, and robust infrastructure for scientific data.
  • The proposed hybrid framework aims to safeguard scientific data as a public good, ensuring accessibility and preservation.