论文标题
使数字对象在高能物理学中公平：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
论文作者
论文摘要
高能物理学（HEP）数据密集型学科的研究通常依赖于域特异性的数字内容。研究的可重复性依赖于这些数字对象的适当保存。本文反映了在这种情况下对可发现性，可访问性，互操作性和可重复性（公平）的原则的解释，并通过描述开发端到端支持基础架构来保存和访问通用Feynrules输出（UFO）模型，以公平原则为指导。不明飞行物模型是HEP社区使用的定制Python库，用于对撞机物理事件的蒙特卡洛模拟。我们的框架提供了简单但坚固的工具，可以根据公平原则保存和访问UFO模型和相应的元数据。
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.
