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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.
Nature Human Behaviour
|December 8, 2020
Summary
This guide offers practical tips for researchers navigating large neuroimaging datasets, covering the entire data lifecycle to enhance accessibility and foster scientific discovery in the open science era.
Area of Science:
- Neuroimaging research
- Data science in neuroscience
Background:
- Increasing availability of large neuroimaging datasets.
- Growing adoption of open science principles in research.
- Challenges faced by novice users with large datasets.
Purpose of the Study:
- Provide practical guidance for end-users working with large neuroimaging datasets.
- Address challenges in data lifecycle management for researchers.
- Facilitate broader scientific discovery through accessible data handling.
Main Methods:
- Data lifecycle management strategies.
- Tips for downloading and storing large datasets.
- Guidance on dataset familiarization and result communication.
Main Results:
- A comprehensive set of practical tips for handling large neuroimaging data.
- Strategies to overcome common difficulties encountered by novice users.
- Framework for effective data sharing and result communication.
Conclusions:
- Democratizing access to large neuroimaging datasets through practical guidance.
- Lowering barriers to entry for researchers utilizing big data.
- Promoting rigorous scientific investigation and discovery in neuroscience.
