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Published on: June 26, 2013
A hitchhiker's guide to working with large, open-source neuroimaging datasets
Corey Horien1,2, Stephanie Noble3, Abigail S Greene4,5
1Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, USA. corey.horien@yale.edu.
Abstract:
Large datasets that enable researchers to perform investigations with unprecedented rigor are growing increasingly common in neuroimaging. Due to the simultaneous increasing popularity of open science, these state-of-the-art datasets are more accessible than ever to researchers around the world. While analysis of these samples has pushed the field forward, they pose a new set of challenges that might cause difficulties for novice users. Here we offer practical tips for working with large datasets from the end-user's perspective. We cover all aspects of the data lifecycle: from what to consider when downloading and storing the data to tips on how to become acquainted with a dataset one did not collect and what to share when communicating results. This manuscript serves as a practical guide one can use when working with large neuroimaging datasets, thus dissolving barriers to scientific discovery.

