Training and onboarding initiatives in high energy physics experiments.

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

Frontiers in Big Data Pub Date : 2025-02-10 eCollection Date: 2025-01-01 DOI:10.3389/fdata.2025.1497622

Allison Reinsvold Hall, Nicole Skidmore, Gabriele Benelli, Ben Carlson, Claire David, Jonathan Davies, Wouter Deconinck, David DeMuth, Peter Elmer, Rocky Bala Garg, Stephan Hageböck, Killian Lieret, Valeriia Lukashenko, Sudhir Malik, Andy Morris, Heidi Schellman, Graeme A Stewart, Jason Veatch, Michel Hernandez Villanueva

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引用次数: 0

Abstract

In this article we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is increasingly important for HEP experiments. With rapidly increasing data volumes and larger collaborations the analyses and consequently, the related software, become ever more complex. This necessitates structured onboarding and training. Recognizing this, a meeting series was held by the HEP Software Foundation (HSF) in 2022 for experiments to showcase their initiatives. Here we document and analyze these in an attempt to determine a set of key considerations for future HEP experiments.

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来源期刊

Frontiers in Big Data Multiple-

CiteScore

5.20

自引率

3.20%

发文量

122

审稿时长

13 weeks