Curation Policy – FAIR² Data Management
Purpose
FAIR² Data Management, powered by Senscience, ensures that every dataset submitted is curated, certified, and preserved to the highest standards of openness, interoperability, and responsible reuse. Our policy guarantees that data remains discoverable, trusted, and reusable for the long term.
Scope
This policy applies to all datasets deposited via FAIR² Data Management and published under the FAIR² open specification, governed by the FAIR² Alliance.
Curation Process
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Initial Submission
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Authors provide datasets and accompanying metadata via the FAIR² submission system.
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Datasets must comply with relevant ethical, legal, and privacy requirements.
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Automated AI Stewardship
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Clara, the world’s first AI Data Steward, automates metadata extraction, compliance checks, and structural validation.
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Automation reduces preparation time while ensuring alignment with FAIR² standards.
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Expert Review
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Curated outputs are reviewed by domain experts for quality, accuracy, and completeness.
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Each dataset may be linked to a peer-reviewed Data Article for scholarly validation.
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Certification & Publication
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Successfully curated datasets receive FAIR² Certification, guaranteeing they are Findable, Accessible, Interoperable, Reusable — and AI-Ready, Responsible, and Reliable.
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Every dataset is published through an interactive portal, ensuring visibility and engagement.
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Preservation & Sustainability
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Data is stored on trusted infrastructure with redundancy and integrity checks.
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Each dataset is registered with DataCite and assigned a Digital Object Identifier (DOI).
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DataCite metadata ensures persistent linking, discoverability, and interoperability across global repositories and scholarly infrastructure.
Ethics & Responsible Data Use
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FAIR² embeds principles of Responsible AI, including privacy, consent, and accountability.
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Sensitive data is curated with appropriate access controls and governance mechanisms.
Contact
Questions about this policy may be directed to:
📧 info@senscience.ai | 🌍 senscience.ai