Ten simple rules for getting and giving credit for data

Abstract

Data is a hot topic and for good reason-it can be challenging to generate, complicated to analyze, difficult to describe, and near impossible to share. But, unlike the scientific publication, data by itself gets almost no credit or recognition beyond a few figures in the paper. However, keeping data hidden until publication delays knowledge transfer and slows down discovery. In addition, the criteria for publication continues to grow more demanding, as does the need to find new ways to share information Imagine if science was able to effectively and efficiently share data in a findable, accessible, interoperable, and reusable (FAIR; [2]) manner outside of a publication, in a way that enables comparability and reproducibility, while also ensuring that the data contributors were appropriately credited for their contributions! Could we worry less about being scooped? Should we embrace data sharing as a desirable criteria, in addition to publishing, during career evaluations [3]? Can we accelerate the process of science?! Good news is some of this is already happening. The rise of preprints has demonstrated that sharing science prior to publication can respect one's individual contribution while also accelerating scientific knowledge transfer For example, rapid dissemination of knowledge via preprints was critical in supporting a rapid response to the recent global pandemic If you are interested in submitting a preprint but don't know where to start, consider the 10 Simple Rules article by Bourne and colleagues In addition to preprints, many publishers support data papers (Nature, Elsevier, Springer, etc.), some research domains have started to advocate for data sharing (e.g., biodiversity; [9-11]), and a few data centers even facilitate data sharing by offering data preprints (e.g., NASA's Distributed Active Archive Centers). In addition, federal agencies, including funders like NSF and NIH, data producers like NASA, and a coalition of scientific societies, publishers, institutions, etc. are beginning to advocate for the practice of referencing or citing data

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