In the last decade, neuroimaging research has seen a proliferation of open tools, platforms, and standards aimed at addressing the reproducibility crisis in the field. The growing awareness on this topic is bringing about a cultural shift in the scientific community, especially among early career researchers (ECRs). As members of this demographic, we can attest to the fact that the adoption of these new tools and practices remains a challenge. This work aims to provide a practical guide for ECRs to navigate the expanding landscape of the open-science resources and make proactive decisions for their research workflows dealing with large, multiple datasets. From our own experience, we describe the common hurdles faced in typical research workflow and provide a set of solutions that could serve as a starting point for researchers looking for practical tools and protocols. Through a hypothetical scenario, we walk through the steps of curating, processing, harmonizing, and publishing a dataset while describing the tools and practices helpful for adopting FAIR (findable, accessible, interoperable, and reusable) principles. We hope this guide can help ECRs and others to simplify their daily research life as we all strive towards more open, reproducible, and translational neuroscience research.
