AUTHOR=Kain Michael, Bodin Marjolaine, Loury Simon, Chi Yao, Louis Julien, Simon Mathieu, Lamy Julien, Barillot Christian, Dojat Michel TITLE=Small Animal Shanoir (SAS) A Cloud-Based Solution for Managing Preclinical MR Brain Imaging Studies JOURNAL=Frontiers in Neuroinformatics VOLUME=14 YEAR=2020 URL=https://www.frontiersin.org/articles/10.3389/fninf.2020.00020 DOI=10.3389/fninf.2020.00020 ISSN=1662-5196 ABSTRACT=Clinical multicenter imaging studies are frequent and rely on a wide range of existing tools for sharing data and processing pipelines. This is not the case for preclinical (small animal) studies. Animal population imaging is still in infancy, especially because a complete standardization and control of initial conditions in animal models across labs is still difficult and few studies aim at standardization of acquisition and post-processing techniques. Clearly, there is a need of appropriate tools for the management and sharing of data, post-processing and analysis methods dedicated to small animal imaging. Solutions developed for Human imaging studies cannot be directly applied to this specific domain. In this paper, we present the Small Animal Shanoir (SAS) solution for supporting animal population imaging using tools compatible with open data. The integration of automated workflow tools ensures accessibility and reproducibility of research outputs. By sharing data and imaging processing tools, hosted by SAS, we promote data preparation and tools for reproducibility and reuse, and participation in multicenter or replication “open science” studies contributing to the improvement of quality science in preclinical domain. SAS is a first step for promoting open science for small animal imaging and a contribution to the valorization of data and pipelines of reference.