An analysis of the effects of sharing research data, code, and preprints on citations
Giovanni Colavizza, Lauren Cadwallader, Marcel LaFlamme, Gr\'egory, Dozot, St\'ephane Lecorney, Daniel Rappo, Iain Hrynaszkiewicz

TL;DR
This study investigates how open science practices like preprints and data sharing influence citation counts, finding that preprints significantly boost citations, data sharing has a smaller positive effect, and sharing code shows no significant impact.
Contribution
It provides empirical evidence on the citation benefits of open science practices across disciplines using a large, novel dataset and rigorous control variables.
Findings
Preprints increase citations by about 20.2%.
Sharing data correlates with a 4.3% citation increase.
Sharing code shows no significant citation effect.
Abstract
Calls to make scientific research more open have gained traction with a range of societal stakeholders. Open Science practices include but are not limited to the early sharing of results via preprints and openly sharing outputs such as data and code to make research more reproducible and extensible. Existing evidence shows that adopting Open Science practices has effects in several domains. In this study, we investigate whether adopting one or more Open Science practices leads to significantly higher citations for an associated publication, which is one form of academic impact. We use a novel dataset known as Open Science Indicators, produced by PLOS and DataSeer, which includes all PLOS publications from 2018 to 2023 as well as a comparison group sampled from the PMC Open Access Subset. In total, we analyze circa 122'000 publications. We calculate publication and author-level citation…
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Taxonomy
TopicsAcademic Publishing and Open Access · scientometrics and bibliometrics research
