As journals attempt to increase the openness and reproducibility of published data through mandatory data sharing policies, researchers from The Alan Turing Institute have examined the nature of data sharing statements and how they affect article impact.

In a preprint published on arXiv.org, researchers categorised the data sharing statements of 531,889 journal articles published by Public Library of Science (PLoS) and BioMed Central (BMC), since the introduction of data sharing policies. (Data sharing statements were required or encouraged from 2011 and mandated in 2015 by BMC, and mandated from 2014 for PLoS.)

Data sharing statements were categorised based on whether underlying data were available via a direct link to a repository, available in the paper or supplementary materials, available upon request, or not available at all. Articles linking to source data repositories were found to make up only a fraction (12–21%) of the total, while the most common data sharing statements encapsulated the default journal guidance wording of ‘not applicable’ or ‘data can be found within the article body or supplementary material’.

The researchers found that articles linking to a data repository had a 25% higher citation count than average. These findings expand on previous studies showing a similar link between open data and impact in other fields, providing evidence of a multi-disciplinary effect.

The authors acknowledge the potential for bias; articles with access to suitable repositories may be more likely to be authored by larger, successful research groups with greater resources at their disposal. However, efforts are underway to overcome these barriers via initiatives such as Dryad and FlowRepository, or journal linked repositories such as figshare.

The authors suggest that sharing data enhances the credibility of an article’s results, as it supports reproducibility, and encourages re-use (which might further contribute to citation counts). As an increasing number of funding bodies require that publications include data sharing statements, these findings illustrate the benefits to authors and researchers.

——————————————————–

Summary by Julianna Solomons PhD, CMPP from Aspire Scientific

——————————————————–

With thanks to our sponsors, Aspire Scientific Ltd and NetworkPharma Ltd