Recent concerns about the reproducibility of science have led to several calls for more open and transparent research practices and for the monitoring of potential improvements over time. However, with tens of thousands of new biomedical articles published per week, manually mapping and monitoring changes in transparency is unrealistic. We present an open-source, automated approach to identify five indicators of transparency (data sharing, code sharing, conflicts of interest disclosures, funding disclosures and protocol registration) and apply it across the entire open access biomedical literature of 2.75 million articles on PubMed Central. Our results indicate remarkable improvements in some (e.g. conflict of interest disclosures, funding disclosures), but not other (e.g. protocol registration, code sharing) areas of transparency over time, and map transparency across fields of science, countries, journals and publishers. This work has enabled the creation of a large, integrated, and openly available database to expedite further efforts to monitor, understand and promote transparency and reproducibility in science.

中文翻译：

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评估生物医学文献中的透明度指标：公开程度如何？

最近对科学可复制性的关注导致了对更加开放和透明的研究实践以及随着时间的推移监测潜在改进的若干呼吁。但是，随着每周发布成千上万的新生物医学文章，手动绘制和监视透明度的变化是不现实的。我们提供一种开源的自动化方法，以识别透明度的五个指标（数据共享，代码共享，利益冲突披露，资金披露和协议注册），并将其应用于PubMed Central上275万篇文章的全部开放获取生物医学文献中。我们的结果表明，随着时间的流逝，某些（例如利益冲突披露，资金披露）进步明显，但其他（例如协议注册，代码共享）透明度却没有改善，并在科学，国家，期刊和出版商之间绘制透明地图。这项工作使得能够创建一个大型的，集成的，可公开使用的数据库，从而加快了进一步努力来监视，理解和促进科学的透明度和可重复性。