A decentralized future for the open-science databases

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.