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<!DOCTYPE HTML>
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<h1 id="fair-principles">FAIR Principles</h1>
<p>Adopting the FAIR principles in your research ensures that your data is well-managed, easily shared, and readily available for future research. More information about the FAIR principles can be found on the <a href="https://www.go-fair.org/fair-principles/">GO FAIR website</a>.</p>
<h2 id="findable">Findable</h2>
<p>Data should be easy to find by both humans and computers. This involves assigning a globally unique and persistent identifier to data, describing data with rich metadata, and indexing metadata in searchable resources. Clear and explicit identifiers should be included in metadata to facilitate search and discovery.</p>
<h2 id="accessible">Accessible</h2>
<p>Once data is found, it should be easy to access. This requires that data and metadata be retrievable via standardized communication protocols, which are open, free, and universally implementable. Where necessary, these protocols should support authentication and authorization. Additionally, metadata should remain accessible even if the data itself is no longer available.</p>
<h2 id="interoperable">Interoperable</h2>
<p>Data should be integrated with other data. This is achieved by using formal, accessible, shared, and widely applicable languages for knowledge representation. Data and metadata should use vocabularies that adhere to FAIR principles, and include qualified references to other data and metadata to ensure consistency and interoperability.</p>
<h2 id="reusable">Reusable</h2>
<p>Data should be reusable for future research. This means data and metadata should be richly described with accurate and relevant attributes. Data should be released with clear and accessible usage licenses, associated with detailed provenance information, and conform to community standards relevant to the domain.</p>
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<p> We would like to express our heartfelt gratitude to <strong>Neurohackademy</strong> at the <strong>University of Washington eScience Institute</strong> for providing invaluable training and support. This experience has significantly enriched our understanding of neuroimaging and data science. We also acknowledge the support of the National Institute of Mental Health (NIMH) grant number <strong>5R25MH112480-08</strong>, which made this opportunity possible.</p>
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