FAIR is everywhere


Implementing FAIR Workflows: A Proof of Concept Study in the Field of Consciousness is a 3-year project funded by the Templeton World Charity Foundation. In this project, DataCite works with a number of partners on providing an exemplar workflow that can be used by researchers to implement FAIR practices throughout their research lifecycle. In this monthly blog series, the different project participants will share perspectives on FAIR practices and recommendations. 

In this second blog post, Helena Cousijn, Director of Community Engagement at DataCite, shares what makes the FAIR workflows project different.

Last month, Zefan Zheng shared his perspective as a Neuroscience PhD student on our blog as part of our FAIR Workflows blog series. Ten years ago, I was a Neuroscience PhD student as well. At the time people were starting to talk about data sharing, but FAIR didn’t exist yet.

Now FAIR is everywhere. For most of the people following the DataCite blog, FAIR is a concept they work with every day. But what does FAIR actually mean for researchers and their workflows? DataCite is involved in many FAIR projects but sometimes it feels as if, despite all the great tools, systems, policies and guidance we’re developing, we’re not getting closer to really incorporating FAIR into the everyday workflows of researchers.

Together with several of our partners, and supported by the Templeton World Charity Foundation (TWCF), we started to discuss if we could change that. Could we do a project where FAIR workflows weren’t an afterthought, but were part of the process before the process had even started? TWCF suggested that the best approach would be to work directly with a research group and suggested the group of Prof. Lucia Melloni (who -small world- I shared an office with for a couple of months 10 years ago).

Together with Lucia and her team, we developed a proposal for a proof of concept study in the field of Consciousness, to be carried out by a new PhD student who would test out approaches to FAIR workflows every step of the way. This would give us the opportunity to work with someone to whom all of this is new, and really see what it means for them to work with FAIR.

Our project seeks to provide an exemplar workflow which will take the concept of making one’s research FAIR and open, and will provide a concrete example and implementation based on the reality of an entire research investigation lifecycle. In doing so, this will test the challenges of the research team, the time investments, the availability of the metadata and tools needed to ensure FAIR research outputs, and the ability of a dashboard to meaningfully capture the research workflow and demonstrate the impact of research outputs. For FAIR workflows to become standard for all researchers, they will need to have examples that are easy to implement of how to make their research outputs FAIR and open, and we hope that this project will be impactful as a demonstration.

We collaborate closely with other FAIR projects, but we hope to add something new through our daily interactions with a researcher. By the end of the project, we hope to have a good understanding of what is and isn’t feasible as part of the daily work of an early career researcher. How much time do open science practices and FAIR workflows actually take? And what are the hurdles? Along the way, we’ll share updates here, so stay tuned! 

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This project was made possible through the support of a grant from Templeton World Charity Foundation, Inc. The opinions expressed in this publication are those of the author(s) and do not necessarily reflect the views of Templeton World Charity Foundation, Inc.

Helena Cousijn
Community Engagement Director at DataCite | Blog posts