FAIR Island: real-world examples of place-based open science

Area of Science:

• Environmental science and open science initiatives.
• Data governance and sustainable development.

Background:

• The FAIR (Findable, Accessible, Interoperable, Reusable) data principles are crucial for open science.
• Extending data principles to include people and place, like the CARE Principles for Indigenous Data Governance, is a growing need.
• Scientific field stations offer infrastructure to implement these extended data principles.

Purpose of the Study:

• To translate data governance ideals into practice using scientific field stations.
• To build interoperability between research infrastructure components and societal benefit areas.
• To accelerate place-based research for sustainable development.

Main Methods:

• Leveraging institutional infrastructure of scientific field stations.
• Using French Polynesian field stations as key use cases connected to international research networks.
• Developing interoperability between research infrastructure and societal benefit applications.

Main Results:

• Increased potential for scientific data reuse and awareness of field station research.
• Established connections between research infrastructure and societal benefit areas.
• Demonstrated a model for place-based research and sustainable development.

Conclusions:

• The FAIR Island project successfully integrates data governance principles with scientific field station infrastructure.
• The project accelerates place-based research and contributes to sustainable development goals.
• FAIR Island provides a scalable model for other long-term scientific study sites.