Making Digital Objects FAIR in High Energy Physics: An Implementation for Universal FeynRules Output (UFO) Models

TL;DR

This paper presents a framework for making digital objects in high energy physics, specifically UFO models used in simulations, more FAIR-compliant to enhance reproducibility and data sharing.

Contribution

It introduces an end-to-end infrastructure that preserves and provides access to UFO models and metadata following FAIR principles in high energy physics.

Findings

Framework enables easy preservation of UFO models.

Supports FAIR principles for better data sharing.

Improves reproducibility of HEP research.

Abstract

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.