Problem
Research questions and friction points this paper is trying to address.
FAIR
metadata
scientific datasets
AI workflows
FOXDEN: FAIR Services for AI-Ready Scientific Datasets
🤖 AI Summary
FOXDEN项目通过提供丰富的机器可读元数据和来源信息，遵循FAIR原则，解决科学数据集与AI工作流兼容性问题。
📝 Abstract
Scientific datasets are most compatible with AI workflows when they are described by rich, machine-readable metadata and provenance information, following the FAIR guiding principles. The FAIR Open-Science Extensible Data Exchange Network (FOXDEN) is a set of cyberinfrastructure building blocks developed at the Cornell High Energy Synchrotron Source (CHESS) for annotating raw, reduced, and analyzed datasets with both structured and unstructured metadata and provenance records. It also allows researchers to publish these records with Digital Object Identifiers (DOIs) to create AI-ready datasets. We describe FOXDEN's architecture and its deployment at CHESS and at the National High Magnetic Field Laboratory, where it serves as a foundation for future agentic scientific workflows.
Innovation
Methods, ideas, or system contributions that make the work stand out.
FAIR
metadata
provenance
cyberinfrastructure
Digital Object Identifiers
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