构建可被人工智能使用的太空生命科学数据系统
Building AI-Ready Data Systems for Space Life Sciences, Aerospace Medicine, and Deep Space Exploration
- 提出从FAIR到AI-ready再到太空就绪的三级数据体系
- 强调现有基础设施需改进以弥合人工智能访问鸿沟
- 建议设立中立国际协调机构保障数据可信与可访问
尽管人工智能有望革新太空生命科学，但实现这一潜力依赖于将异构航天生物学数据系统性重构为机器可操作的AI就绪形式。即使开放获取原则支持人类重用和科学可复现性，也不一定使AI系统能访问和分析这些多样化科学数据集。随着人工智能方法的不断增多，对数据结构、元数据和访问接口提出了不同要求。为此，我们提出从FAIR到AI-ready再到空间就绪的三级推进策略，并讨论现有基础设施如何改进以缩小AI访问差距。最后，我们提议建立一个中立的国际协调机构，作为深空生物学研究所需可信、代理可访问空间生物学基础设施的治理核心。
原文摘要 · Abstract (English)
While AI holds the potential to revolutionize space life sciences, realizing this promise is contingent upon the systematic restructuring of heterogeneous spaceflight biological data into machine-actionable, AI-ready forms. Even though open access principles support human reuse and scientific reproducibility, this does not necessarily enable AI systems to access and analyze such a diverse set of scientific datasets. In addition, the growing array of AI approaches places distinct demands on data structure, metadata, and access interfaces. In order to respond to such growing changes we propose a three-tier approach, proceeding from FAIR to AI-ready to space-ready data. We discuss existing infrastructures and how they can be improved to close the AI access gap. We conclude by proposing a neutral international coordinating body as the governance backbone for the trustworthy, agent-accessible space biology infrastructure that deep space biological research will require.
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