Training and onboarding initiatives in high energy physics experiments

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

doi:10.3389/fdata.2025.1497622

Training and onboarding initiatives in high energy physics experiments

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

Physics

Research output: Contribution to journal › Review article › peer-review

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.

Original language	English (US)
Article number	1497622
Journal	Frontiers in Big Data
Volume	8
DOIs	https://doi.org/10.3389/fdata.2025.1497622
State	Published - 2025

All Science Journal Classification (ASJC) codes

Computer Science (miscellaneous)
Information Systems
Artificial Intelligence

Keywords

analysis software
data analysis
high energy physics
onboarding
particle physics
scientific computing
training

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10.3389/fdata.2025.1497622

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Reinsvold Hall, A., Skidmore, N., Benelli, G., Carlson, B., David, C., Davies, J., Deconinck, W., DeMuth, D., Elmer, P., Garg, R. B., Hageböck, S., Lieret, K., Lukashenko, V., Malik, S., Morris, A., Schellman, H., Stewart, G. A., Veatch, J., & Hernandez Villanueva, M. (2025). Training and onboarding initiatives in high energy physics experiments. Frontiers in Big Data, 8, Article 1497622. https://doi.org/10.3389/fdata.2025.1497622

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title = "Training and onboarding initiatives in high energy physics experiments",

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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author = "{Reinsvold Hall}, Allison and Nicole Skidmore and Gabriele Benelli and Ben Carlson and Claire David and Jonathan Davies and Wouter Deconinck and David DeMuth and Peter Elmer and Garg, {Rocky Bala} and Stephan Hageb{\"o}ck and Killian Lieret and Valeriia Lukashenko and Sudhir Malik and Andy Morris and Heidi Schellman and Stewart, {Graeme A.} and Jason Veatch and {Hernandez Villanueva}, Michel",

note = "Publisher Copyright: Copyright {\textcopyright} 2025 Reinsvold Hall, Skidmore, Benelli, Carlson, David, Davies, Deconinck, DeMuth, Elmer, Garg, Hageb{\"o}ck, Lieret, Lukashenko, Malik, Morris, Schellman, Stewart, Veatch and Hernandez Villanueva.",

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doi = "10.3389/fdata.2025.1497622",

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journal = "Frontiers in Big Data",

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Reinsvold Hall, A, Skidmore, N, Benelli, G, Carlson, B, David, C, Davies, J, Deconinck, W, DeMuth, D, Elmer, P, Garg, RB, Hageböck, S, Lieret, K, Lukashenko, V, Malik, S, Morris, A, Schellman, H, Stewart, GA, Veatch, J & Hernandez Villanueva, M 2025, 'Training and onboarding initiatives in high energy physics experiments', Frontiers in Big Data, vol. 8, 1497622. https://doi.org/10.3389/fdata.2025.1497622

TY - JOUR

T1 - Training and onboarding initiatives in high energy physics experiments

AU - Reinsvold Hall, Allison

AU - Skidmore, Nicole

AU - Benelli, Gabriele

AU - Carlson, Ben

AU - David, Claire

AU - Davies, Jonathan

AU - Deconinck, Wouter

AU - DeMuth, David

AU - Elmer, Peter

AU - Garg, Rocky Bala

AU - Hageböck, Stephan

AU - Lieret, Killian

AU - Lukashenko, Valeriia

AU - Malik, Sudhir

AU - Morris, Andy

AU - Schellman, Heidi

AU - Stewart, Graeme A.

AU - Veatch, Jason

AU - Hernandez Villanueva, Michel

N1 - Publisher Copyright: Copyright © 2025 Reinsvold Hall, Skidmore, Benelli, Carlson, David, Davies, Deconinck, DeMuth, Elmer, Garg, Hageböck, Lieret, Lukashenko, Malik, Morris, Schellman, Stewart, Veatch and Hernandez Villanueva.

PY - 2025

Y1 - 2025

N2 - 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.

AB - 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.

KW - analysis software

KW - data analysis

KW - high energy physics

KW - onboarding

KW - particle physics

KW - scientific computing

KW - training

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JO - Frontiers in Big Data

JF - Frontiers in Big Data

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ER -

Training and onboarding initiatives in high energy physics experiments

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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