Open science saves lives: lessons from the COVID-19 pandemic
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Abstract
In the last decade Open Science principles have been successfully advocated for and are being slowly adopted in different research communities. In response to the COVID-19 pandemic many publishers and researchers have sped up their adoption of Open Science practices, sometimes embracing them fully and sometimes partially or in a sub-optimal manner. In this article, we express concerns about the violation of some of the Open Science principles and its potential impact on the quality of research output. We provide evidence of the misuses of these principles at different stages of the scientific process. We call for a wider adoption of Open Science practices in the hope that this work will encourage a broader endorsement of Open Science principles and serve as a reminder that science should always be a rigorous process, reliable and transparent, especially in the context of a pandemic where research findings are being translated into practice even more rapidly. We provide all data and scripts at https://osf.io/renxy/ .
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SciScore for 10.1101/2020.08.13.249847: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtranspar…SciScore for 10.1101/2020.08.13.249847: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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Excerpt
To close the door on a pandemic, make science more open
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SciScore for 10.1101/2020.08.13.249847: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement More specifically, among these 8 publications, 2 (25.0%) papers were retracted, at the authors’ request, in order to conduct further data analyses and 6 (75.0%) were retracted because the methodology or the data analysis was wrong. 31] were not those listed on the EU Clinical Trials Register. 31], consent was not obtained from patients before they participated in the study or their data were analysed. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The methodology is described in an appendix to this paper, and all the scripts Figure 3: … SciScore for 10.1101/2020.08.13.249847: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement More specifically, among these 8 publications, 2 (25.0%) papers were retracted, at the authors’ request, in order to conduct further data analyses and 6 (75.0%) were retracted because the methodology or the data analysis was wrong. 31] were not those listed on the EU Clinical Trials Register. 31], consent was not obtained from patients before they participated in the study or their data were analysed. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources The methodology is described in an appendix to this paper, and all the scripts Figure 3: Proportion of ArXiv preprints shared in the media, broken down by research topic. ArXivsuggested: (arXiv, RRID:SCR_006500)We then queried the altmetric API for each of these preprints using a Python script to process all entries, find their DOI and query Altmetric with the following command: #i f t h e paper i s not from a r x i v r e q u e s t s . Pythonsuggested: (IPython, RRID:SCR_001658)g e t ( ‘ h t t p s : / / a p i . a l t m e t r i c . com/ v1 / a r x i v /entry_DOI ’ ) Analysis codes are available on the GitHub repository of the project: https://github.com/lonnibesancon/OpenSciencePandemic PubMed Central analysis To extract the reviewing times, the metadata of 12,682 COVID-19 articles were downloaded on July 7, 2020 from PubMed Central using the query: “COVID-19”[abstract] OR “COVID-2019"[abstract] OR “severe acute respiratory syndrome coronavirus 2”[Supplementary Concept] OR “severe acute respiratory syndrome coronavirus 2"[abstract] OR “2019-nCoV”[abstract] OR “SARS-CoV-2"[abstract] OR “2019nCoV”[abstract] OR ((“Wuhan”[abstract] AND (“coronavirus”[MeSH Terms] OR “coronavirus”[abstract])) AND (2019/12[PDAT] OR 2020[PDAT])) The reviewing times were extracted from the data using a MATLAB script, available on the OSF repository. PubMedsuggested: (PubMed, RRID:SCR_004846)MeSHsuggested: (MeSH, RRID:SCR_004750)MATLABsuggested: (MATLAB, RRID:SCR_001622)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.
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