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Abstract #5213

AFQ-Browser: Supporting reproducible human neuroscience research through browser-based visualization tools

Jason Yeatman1,2, Adam Richie-Halford3, Josh Kenyon Smith4, Anisha Keshavan1,5, and Ariel Rokem5

1Institute for Learning and Brain Sciences, The University of Washington, Seattle, WA, United States, 2Department of Speech and Hearing Sciences, The University of Washington, Seattle, WA, United States, 3The Department of Physics, The University of Washington, Seattle, WA, United States, 4Department of Chemical Engineering, The University of Washington, Seattle, WA, United States, 5eScience Institute, The University of Washington, Seattle, WA, United States

MRI research faces various challenges with regards to reproducibility: scientists are generally aware that data sharing is an important component of reproducible research, but it is not always clear how to share data in a manner that allows other researchers to understand and reproduce published findings. Here we describe AFQ-Browser, a software tool that builds an interactive website as a companion to a diffusion MRI study and leverages web-visualization technologies to create linked views between different aspects of a diffusion MRI dataset (anatomy, diffusion metrics, subject metadata). This facilitates exploratory data analysis, fueling new scientific discoveries based on previously published datasets.

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