This guide aims to promote the FAIR data principles and to encourage their adoption by the bioimaging community. We will start by describing what are the FAIR principles, and suggest optional activities as 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/ This document is [a component of Top 10 FAIR things](https://doi.org/10.5281/zenodo.2555498). The working draft started as part of the Mozilla / Library Carpentry sprint 30-31 May 2019. This project holds the preprint document. The document has been evolving between June and September 2019. We offer a variety of format options for the selection of the reader. Last updated on 13 September 2019. Please cite and share this work with [DOI 10.17605/OSF.IO/ZKJ4R](https://osf.io/zkj4r/) Martinez, et al (2019) 10 FAIR for imaging. Open Science Framework pre-print.