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


Abstract

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.

Citation

@articleKiar_2017 doi: 10.1093/gigascience/gix013 url: https://doi.org/10.1093/gigascience/gix013 year: 2017 month: mar publisher: Oxford University Press (OUP) volume: 6 number: 5 author: Kiar Gregory and Gorgolewski Krzysztof J. and Kleissas Dean and Roncal William Gray and Litt Brian and Wandell Brian and Poldrack Russel A. and Wiener Martin and Vogelstein R. Jacob and Burns Randal and Vogelstein Joshua T. title: Science in the cloud (SIC): A use case in MRI connectomics journal: GigaScience

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