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Science in the cloud (SIC): A use case in MRI connectomics

Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardize...

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Autores principales: Kiar, Gregory, Gorgolewski, Krzysztof J., Kleissas, Dean, Roncal, William Gray, Litt, Brian, Wandell, Brian, Poldrack, Russel A., Wiener, Martin, Vogelstein, R. Jacob, Burns, Randal, Vogelstein, Joshua T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467033/
https://www.ncbi.nlm.nih.gov/pubmed/28327935
http://dx.doi.org/10.1093/gigascience/gix013
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author Kiar, Gregory
Gorgolewski, Krzysztof J.
Kleissas, Dean
Roncal, William Gray
Litt, Brian
Wandell, Brian
Poldrack, Russel A.
Wiener, Martin
Vogelstein, R. Jacob
Burns, Randal
Vogelstein, Joshua T.
author_facet Kiar, Gregory
Gorgolewski, Krzysztof J.
Kleissas, Dean
Roncal, William Gray
Litt, Brian
Wandell, Brian
Poldrack, Russel A.
Wiener, Martin
Vogelstein, R. Jacob
Burns, Randal
Vogelstein, Joshua T.
author_sort Kiar, Gregory
collection PubMed
description Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called ‘science in the cloud’ (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended.
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spelling pubmed-54670332017-06-19 Science in the cloud (SIC): A use case in MRI connectomics Kiar, Gregory Gorgolewski, Krzysztof J. Kleissas, Dean Roncal, William Gray Litt, Brian Wandell, Brian Poldrack, Russel A. Wiener, Martin Vogelstein, R. Jacob Burns, Randal Vogelstein, Joshua T. Gigascience Research Modern technologies are enabling scientists to collect extraordinary amounts of complex and sophisticated data across a huge range of scales like never before. With this onslaught of data, we can allow the focal point to shift from data collection to data analysis. Unfortunately, lack of standardized sharing mechanisms and practices often make reproducing or extending scientific results very difficult. With the creation of data organization structures and tools that drastically improve code portability, we now have the opportunity to design such a framework for communicating extensible scientific discoveries. Our proposed solution leverages these existing technologies and standards, and provides an accessible and extensible model for reproducible research, called ‘science in the cloud’ (SIC). Exploiting scientific containers, cloud computing, and cloud data services, we show the capability to compute in the cloud and run a web service that enables intimate interaction with the tools and data presented. We hope this model will inspire the community to produce reproducible and, importantly, extensible results that will enable us to collectively accelerate the rate at which scientific breakthroughs are discovered, replicated, and extended. Oxford University Press 2017-03-07 /pmc/articles/PMC5467033/ /pubmed/28327935 http://dx.doi.org/10.1093/gigascience/gix013 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Kiar, Gregory
Gorgolewski, Krzysztof J.
Kleissas, Dean
Roncal, William Gray
Litt, Brian
Wandell, Brian
Poldrack, Russel A.
Wiener, Martin
Vogelstein, R. Jacob
Burns, Randal
Vogelstein, Joshua T.
Science in the cloud (SIC): A use case in MRI connectomics
title Science in the cloud (SIC): A use case in MRI connectomics
title_full Science in the cloud (SIC): A use case in MRI connectomics
title_fullStr Science in the cloud (SIC): A use case in MRI connectomics
title_full_unstemmed Science in the cloud (SIC): A use case in MRI connectomics
title_short Science in the cloud (SIC): A use case in MRI connectomics
title_sort science in the cloud (sic): a use case in mri connectomics
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5467033/
https://www.ncbi.nlm.nih.gov/pubmed/28327935
http://dx.doi.org/10.1093/gigascience/gix013
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