Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging

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Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging. / Souter, Nicholas E.; Lannelongue, Loïc; Samuel, Gabrielle; Racey, Chris; Colling, Lincoln J.; Bhagwat, Nikhil; Selvan, Raghavendra; Rae, Charlotte L.

I: Imaging Neuroscience, Bind 1, 2023, s. 1-15.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt

Harvard

Souter, NE, Lannelongue, L, Samuel, G, Racey, C, Colling, LJ, Bhagwat, N, Selvan, R & Rae, CL 2023, 'Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging', Imaging Neuroscience, bind 1, s. 1-15. https://doi.org/10.1162/imag_a_00043

APA

Souter, N. E., Lannelongue, L., Samuel, G., Racey, C., Colling, L. J., Bhagwat, N., Selvan, R., & Rae, C. L. (2023). Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging. Imaging Neuroscience, 1, 1-15. https://doi.org/10.1162/imag_a_00043

Vancouver

Souter NE, Lannelongue L, Samuel G, Racey C, Colling LJ, Bhagwat N o.a. Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging. Imaging Neuroscience. 2023;1:1-15. https://doi.org/10.1162/imag_a_00043

Author

Souter, Nicholas E. ; Lannelongue, Loïc ; Samuel, Gabrielle ; Racey, Chris ; Colling, Lincoln J. ; Bhagwat, Nikhil ; Selvan, Raghavendra ; Rae, Charlotte L. / Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging. I: Imaging Neuroscience. 2023 ; Bind 1. s. 1-15.

Bibtex

@article{2e847d686c464eef9c7753debb1596c0,
title = "Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging",
abstract = "Given that scientific practices contribute to the climate crisis, scientists should reflect on the planetary impact of their work. Research computing can have a substantial carbon footprint in cases where researchers employ computationally expensive processes with large amounts of data. Analysis of human neuroimaging data, such as Magnetic Resonance Imaging brain scans, is one such case. Here, we consider ten ways in which those who conduct human neuroimaging research can reduce the carbon footprint of their research computing, by making adjustments to the ways in which studies are planned, executed, and analysed; as well as where and how data are stored.",
author = "Souter, {Nicholas E.} and Lo{\"i}c Lannelongue and Gabrielle Samuel and Chris Racey and Colling, {Lincoln J.} and Nikhil Bhagwat and Raghavendra Selvan and Rae, {Charlotte L.}",
year = "2023",
doi = "10.1162/imag_a_00043",
language = "English",
volume = "1",
pages = "1--15",
journal = "Imaging Neuroscience",
issn = "2837-6056",
publisher = "MIT Press",

}

RIS

TY - JOUR

T1 - Ten recommendations for reducing the carbon footprint of research computing in human neuroimaging

AU - Souter, Nicholas E.

AU - Lannelongue, Loïc

AU - Samuel, Gabrielle

AU - Racey, Chris

AU - Colling, Lincoln J.

AU - Bhagwat, Nikhil

AU - Selvan, Raghavendra

AU - Rae, Charlotte L.

PY - 2023

Y1 - 2023

N2 - Given that scientific practices contribute to the climate crisis, scientists should reflect on the planetary impact of their work. Research computing can have a substantial carbon footprint in cases where researchers employ computationally expensive processes with large amounts of data. Analysis of human neuroimaging data, such as Magnetic Resonance Imaging brain scans, is one such case. Here, we consider ten ways in which those who conduct human neuroimaging research can reduce the carbon footprint of their research computing, by making adjustments to the ways in which studies are planned, executed, and analysed; as well as where and how data are stored.

AB - Given that scientific practices contribute to the climate crisis, scientists should reflect on the planetary impact of their work. Research computing can have a substantial carbon footprint in cases where researchers employ computationally expensive processes with large amounts of data. Analysis of human neuroimaging data, such as Magnetic Resonance Imaging brain scans, is one such case. Here, we consider ten ways in which those who conduct human neuroimaging research can reduce the carbon footprint of their research computing, by making adjustments to the ways in which studies are planned, executed, and analysed; as well as where and how data are stored.

U2 - 10.1162/imag_a_00043

DO - 10.1162/imag_a_00043

M3 - Journal article

VL - 1

SP - 1

EP - 15

JO - Imaging Neuroscience

JF - Imaging Neuroscience

SN - 2837-6056

ER -

ID: 383012515