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Open and reproducible neuroimaging: From study inception to publication
- Niso, Guiomar;
- Botvinik-Nezer, Rotem;
- Appelhoff, Stefan;
- De La Vega, Alejandro;
- Esteban, Oscar;
- Etzel, Joset A;
- Finc, Karolina;
- Ganz, Melanie;
- Gau, Rémi;
- Halchenko, Yaroslav O;
- Herholz, Peer;
- Karakuzu, Agah;
- Keator, David B;
- Markiewicz, Christopher J;
- Maumet, Camille;
- Pernet, Cyril R;
- Pestilli, Franco;
- Queder, Nazek;
- Schmitt, Tina;
- Sójka, Weronika;
- Wagner, Adina S;
- Whitaker, Kirstie J;
- Rieger, Jochem W
- et al.
Published Web Location
https://doi.org/10.1016/j.neuroimage.2022.119623Abstract
Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.
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