RT Journal Article
SR Electronic
T1 AFQ-Browser: Supporting reproducible human neuroscience research through browser-based visualization tools
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 182402
DO 10.1101/182402
A1 Jason D. Yeatman
A1 Adam Richie-Halford
A1 Josh K. Smith
A1 Ariel Rokem
YR 2017
UL http://biorxiv.org/content/early/2017/08/30/182402.abstract
AB Human neuroscience research faces several challenges with regards to reproducibility. While scientists are generally aware that data sharing is an important component of reproducible research, it is not always clear how to usefully share data in a manner that allows other labs to understand and reproduce published findings. Here we describe a new tool, AFQ-Browser, that builds an interactive website as a companion to a published diffusion MRI study. Because AFQ-browser is portable -- it runs in any modern web-browser -- it can facilitate transparency and data sharing. Moreover, by leveraging new web-visualization technologies to create linked views between different dimensions of a diffusion MRI dataset (anatomy, quantitative diffusion metrics, subject metadata), AFQ-Browser facilitates exploratory data analysis, fueling new scientific discoveries based on previously published datasets. In an era where Big Data is playing an increasingly prominent role in scientific discovery, so will browser-based tools for exploring high-dimensional datasets, communicating scientific discoveries, sharing and aggregating data across labs, and publishing data alongside manuscripts.