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

Abstract The relationship between people, place, and data presents challenges and opportunities for science and society. While there has been general enthusiasm for and work toward Findable, Accessible, Interoperable, and Reusable (FAIR) data for open science, only more recently have these data-cent...

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Published in:Gigascience Vol. 12
Main Authors: Robinson, Erin, Buys, Matthew, Chodacki, John, Garzas, Kristian, Monfort, Steven, Nancarrow, Catherine, Praetzellis, Maria, Riley, Brian, Wimalaratne, Sarala, Davies, Neil
Format: Journal Article
Language:English
Published: United States Oxford University Press 20-03-2023
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Summary:Abstract The relationship between people, place, and data presents challenges and opportunities for science and society. While there has been general enthusiasm for and work toward Findable, Accessible, Interoperable, and Reusable (FAIR) data for open science, only more recently have these data-centric principles been extended into dimensions important to people and place—notably, the CARE Principles for Indigenous Data Governance, which affect collective benefit, authority to control, responsibility, and ethics. The FAIR Island project seeks to translate these ideals into practice, leveraging the institutional infrastructure provided by scientific field stations. Starting with field stations in French Polynesia as key use cases that are exceptionally well connected to international research networks, FAIR Island builds interoperability between different components of critical research infrastructure, helping connect these to societal benefit areas. The goal is not only to increase reuse of scientific data and the awareness of work happening at the field stations but more generally to accelerate place-based research for sustainable development. FAIR Island works reflexively, aiming to scale horizontally through networks of field stations and to serve as a model for other sites of intensive long-term scientific study.
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ISSN:2047-217X
2047-217X
DOI:10.1093/gigascience/giad004