An analysis of the effects of sharing research data, code, and preprints on citations
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arXiv
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| Format: | Preprint |
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2024
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| author | Colavizza, Giovanni Cadwallader, Lauren LaFlamme, Marcel Dozot, Grégory Lecorney, Stéphane Rappo, Daniel Hrynaszkiewicz, Iain |
| author_facet | Colavizza, Giovanni Cadwallader, Lauren LaFlamme, Marcel Dozot, Grégory Lecorney, Stéphane Rappo, Daniel Hrynaszkiewicz, Iain |
| contents | 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 indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average. However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_16171 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | An analysis of the effects of sharing research data, code, and preprints on citations Colavizza, Giovanni Cadwallader, Lauren LaFlamme, Marcel Dozot, Grégory Lecorney, Stéphane Rappo, Daniel Hrynaszkiewicz, Iain Digital Libraries 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 indicators and use a broad set of control variables to isolate the effect of Open Science Indicators on received citations. We show that Open Science practices are adopted to different degrees across scientific disciplines. We find that the early release of a publication as a preprint correlates with a significant positive citation advantage of about 20.2% on average. We also find that sharing data in an online repository correlates with a smaller yet still positive citation advantage of 4.3% on average. However, we do not find a significant citation advantage for sharing code. Further research is needed on additional or alternative measures of impact beyond citations. Our results are likely to be of interest to researchers, as well as publishers, research funders, and policymakers. |
| title | An analysis of the effects of sharing research data, code, and preprints on citations |
| topic | Digital Libraries |
| url | https://arxiv.org/abs/2404.16171 |