One of the main goals of applying the FAIR principles to datasets is to enable their reuse. But what criteria must data meet to be considered reusable? To address this question, we implemented the ROADS project (Reusing Openly available Data for Student theses) at the ZHAW Zurich University of Applied Sciences. 

In this project, we examined various use cases in which ZHAW student at different levels (Bachelor’s, Master’s, and PhD) and across disciplines reused existing datasets for their theses, term papers, and other assignments. Specifically, we explored where and why data reuse succeeded and where it encountered obstacles.

In this contribution, we will present these insights and propose recommendations on what should be taken into account to enhance the reusability of future openly available datasets. 

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