Bush-2022

Lessons Learned: A Neuroimaging Research Center’s Transition to Open and Reproducible Science

Github - open-source code, version control, collaboration - analysing
Python - open-source programming - analysing
R - open-source programming - analysing
arXiv/bioRxiv/psyRxiv - preprint sharing - disseminating
OpenNeuro - data sharing - disseminating
Open Science Framework - preregistration - planning
clinicaltrials.gov - preregistration - planning
FAIR (findability”, “accessibility”, “interoperability”, and “reusability”) -principles to organize data, not a tool per se, but I think they need to be emphasized - data collection, organization and sharing -
Brain imaging data structure (BIDS) - a common and standardized framework all scientists can work on - data collection and sharing
Containarized pipelines - code that allows easy reproduction - data analysis
ReproBIDS - dictionary with standardized terms for BIDS neuro data - planning, data collection, data deposition

The steps below were identified after: 1) assessing the crisis of reproducibility, 2) literature search (systematic review) #worth noting since it pops up in so many papers as a previous step to implementation.
hypothesis - experiment - data collection - data analysis - reporting

publish code, publishing pre-prints, standardizing data to BIDS, transition to containarized pipelines, publish data in repositories, establish data dictionaries, pre-registration,

people in the organization need to learn additional programming, version control, and data management skills and work with unfamiliar naming conventions and directory structures mandated by the used standards

costs of effort to be borne by individuals already engaged in challenging, time-consuming work
during transition, the research productivity will suffer