Collaborate review Top 10 FAIR things for imaging

[orchid00]

Top 10 FAIR things for imaging

Project Description

This document aims to promote the use of FAIR principles in the bioimaging community. We will start by describing what are the FAIR principles, and then linking questions to examples of application. This guide is to enhance research data quality and empower researchers, scientists and health professionals to incorporate best data practices throughout the research cycle.
This is a continuation of Top 10 FAIR Data & Software Things
https://www.go-fair.org/2019/02/20/top-10-fair-data-software-things-published/

To inform data producers and data users about the FAIR principles applied to imaging and suggest activities to apply to their research.

Skills required to participate

Anyone should be able to read and provide all kinds all feedback, I welcome more activities to be added and examples and resources.

Integration

How would your project integrate a neuroimager/clinician/psychologist/computational scientist?
the top 10 FAIR things for imaging is a broad but simple guide

Preparation material

have a look https://osf.io/preprints/xs9nh/

how to contribute

I'm looking for reviewers until end of june 2019

Communication

please email me, you can find my email in the document

https://osf.io/preprints/xs9nh/

[orchid00]

Updates!
The project has now been moved to github along with the other domain specific guides
https://librarycarpentry.org/Top-10-FAIR/2019/06/27/imaging/

I'll do my best to keep an updated version in the project folder https://osf.io/preprints/xs9nh/ with multiple formats attached. And the single preprint file https://osf.io/zkj4r/ in odt (OpenDocument Text)