Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form

A Hitchhiker’s Guide to OpenNeuro: Secondary Analysis on the Web’s Largest Repository of Open Neuroimaging Data

Buckser, Rae R. (2022) A Hitchhiker’s Guide to OpenNeuro: Secondary Analysis on the Web’s Largest Repository of Open Neuroimaging Data. Master's Thesis, University of Pittsburgh. (Unpublished)

This is the latest version of this item.

[img]
Preview
PDF
Download (2MB) | Preview

Abstract

Functional MRI (fMRI) is a foundational tool of cognitive neuroscience, but logistical constraints shut many researchers out of data collection. Secondary analysis of open data is a way for researchers to develop novel fMRI analysis methods, ask original questions, and contribute to the neuroimaging literature without collecting new data. To date, much of the documentation and guidance available for working with open neuroimaging data has focused on replication or on secondary analysis of large datasets. There is a lack of concrete, helpful material available for research groups who wish to enable secondary analysis by sharing smaller-scale datasets, or for researchers who wish to use smaller open datasets for their own projects. This document attempts to bridge this gap by offering examples, general recommendations, and concrete guidelines for users and sharers on OpenNeuro, the largest online data repository exclusive to neuroimaging. For users, important considerations include carefully planning analyses and checking preliminary results before committing to downloading and analyzing a dataset. For sharers, important considerations include looking at documentation and supplemental files from a user’s point of view. The accompanying appendices offer checklists designed to walk researchers through the process of uploading data to share or using OpenNeuro data in four basic fMRI analysis tasks. Using and sharing open neuroimaging data represents an investment in a field that has become more collaborative than ever before. The guidance and perspective offered should help users and sharers to make a productive start at navigating the open data landscape with OpenNeuro.


Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Buckser, Rae R.buckser@pitt.edubuckser0000-0002-3383-7494
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairCoutanche, Marc N.marc.coutanche@pitt.edumarc.coutanche
Committee MemberFiez, Julie A.fiez@pitt.edufiez
Committee MemberCalabro, Finnegan J.fjc20@pitt.edufjc20
Date: 21 March 2022
Date Type: Publication
Defense Date: 1 December 2021
Approval Date: 21 March 2022
Submission Date: 10 January 2022
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 104
Institution: University of Pittsburgh
Schools and Programs: Dietrich School of Arts and Sciences > Psychology
Degree: MS - Master of Science
Thesis Type: Master's Thesis
Refereed: Yes
Uncontrolled Keywords: functional MRI; fMRI; open neuroimaging; open data; data-sharing; functional neuroimaging; guidance; data sharing checklist; functional neuroimaging; neuroimaging; data; big data; data repositories; datasets; fMRI methods; open science
Date Deposited: 21 Mar 2022 17:12
Last Modified: 21 Mar 2022 17:12
URI: http://d-scholarship.pitt.edu/id/eprint/42175

Available Versions of this Item


Metrics

Monthly Views for the past 3 years

Plum Analytics


Actions (login required)

View Item View Item