高能物理数字对象FAIR的制作：通用FeynRules输出（UFO）模型的实现
Making Digital Objects FAIR in High Energy Physics: An Implementation for Universal FeynRules Output (UFO) Models
摘要：
高能物理（HEP）的数据密集型学科的研究往往依赖于特定领域的数字内容。研究成果的复制依赖于对这些数字对象的妥善保存。本文反映了在这种情况下的可查找性，可访问性，互操作性和可重用性（FAIR）的原则的解释，并通过描述一个端到端的支持基础设施的发展，维护和访问通用费恩规则输出（UFO）模型的指导下，FAIR原则，展示了其实施。UFO模型是HEP社区用于对撞机物理事件的蒙特卡罗模拟的定制Python库。我们的框架提供了简单但强大的工具来保存和访问UFO模型和相应的元数据按照公平的原则。
英文摘要：
Research in the data-intensive discipline of high energy physics (HEP) often relies on domain-specific digital contents. Reproducibility of research relies on proper preservation of these digital objects. This paper reflects on the interpretation of principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) in such context and demonstrates its implementation by describing the development of an end-to-end support infrastructure for preserving and accessing Universal FeynRules Output (UFO) models guided by the FAIR principles. UFO models are custom-made python libraries used by the HEP community for Monte Carlo simulation of collider physics events. Our framework provides simple but robust tools to preserve and access the UFO models and corresponding metadata in accordance with the FAIR principles.
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