ABSTRACT
BackgroundAs per the FAIR principles (Findable, Accessible, Interoperable, and Reusable), scientific research data should be findable, accessible, interoperable, and reusable. The COVID-19 pandemic has led to massive research activities and an unprecedented number of topical publications in a short time. There has not been any evaluation to assess if this COVID-19-related research data complied with FAIR principles (or FAIRness) so far. ObjectiveOur objective was to investigate the availability of open data in COVID-19-related research and to assess compliance with FAIRness. MethodsWe conducted a comprehensive search and retrieved all open-access articles related to COVID-19 from journals indexed in PubMed, available in the Europe PubMed Central database, published from January 2020 through June 2023, using the metareadr package. Using rtransparent, a validated automated tool, we identified articles that included a link to their raw data hosted in a public repository. We then screened the link and included those repositories which included data specifically for their pertaining paper. Subsequently, we automatically assessed the adherence of the repositories to the FAIR principles using FAIRsFAIR Research Data Object Assessment Service (F-UJI) and rfuji package. The FAIR scores ranged from 1-22 and had four components. We reported descriptive analysis for each article type, journal category and repository. We used linear regression models to find the most influential factors on the FAIRness of data. Results5,700 URLs were included in the final analysis, sharing their data in a general-purpose repository. The mean (standard deviation, SD) level of compliance with FAIR metrics was 9.4 (4.88). The percentages of moderate or advanced compliance were as follows: Findability: 100.0%, Accessibility: 21.5%, Interoperability: 46.7%, and Reusability: 61.3%. The overall and component-wise monthly trends were consistent over the follow-up. Reviews (9.80, SD=5.06, n=160), and articles in dental journals (13.67, SD=3.51, n=3) and Harvard Dataverse (15.79, SD=3.65, n=244) had the highest mean FAIRness scores, whereas letters (7.83, SD=4.30, n=55), articles in neuroscience journals (8.16, SD=3.73, n=63), and those deposited in GitHub (4.50, SD=0.13, n=2,152) showed the lowest scores. Regression models showed that the most influential factor on FAIRness scores was the repository (R2=0.809). ConclusionThis paper underscored the potential for improvement across all facets of FAIR principles, with a specific emphasis on enhancing Interoperability and Reusability in the data shared within general repositories during the COVID-19 pandemic.
Subject(s)
COVID-19ABSTRACT
Background Mandates and recommendations related to embedding open science practices within the research lifecycle are increasingly common. Few stakeholders, however, are monitoring compliance to their mandates or recommendations. It is necessary to monitor the current state of open science to track changes over time and to identify areas to create interventions to drive improvements. Monitoring open science practices requires that they are defined and operationalized. Involving the biomedical community, we sought to reach consensus on a core set of open science practices to monitor at biomedical research institutions. Methods and Findings To establish consensus in a structured and systematic fashion, we conducted a modified 3-round Delphi study. Participants in Round 1 were 80 individuals from 20 biomedical research institutions that exhibit interest in or actively support open science. Participants were research administrators, researchers, specialists in dedicated open science roles, and librarians. In Rounds 1 and 2, participants completed an online survey evaluating a set of potential open science practices that could be important and meaningful to monitor in an automated institutional open science dashboard. Participants voted on the inclusion of each item and provided a rationale for their choice. We defined consensus as 80% agreement. Between rounds, participants received aggregated voting scores for each item and anonymized comments from all participants, and were asked to re-vote on items that did not reach consensus. For Round 3, we hosted two half- day virtual meetings with 21 and 17 participants respectively to discuss and vote on all items that had not reached consensus after Round 2. Ultimately, participants reached consensus to include a 19 open science practices. Conclusions A group of international stakeholders used a modified Delphi process to agree upon open science practices to monitor in a proposed open science dashboard for biomedical institutions. The core set of 19 open science practices identified by participants will form the foundation for institutional dashboards that display compliance with open science practices. They will now be assessed and tested for automatic inclusion in terms of technical feasibility. Using user-centered design, participating institutions will be involved in creating a dashboard prototype, which can then be implemented to monitor rates of open science practices at biomedical institutions. Our methods and approach may also transfer to other research settings–other disciplines could consider using our consensus list as a starting point for agreement upon a discipline-specific set of open science practices to monitor. The findings may also be of broader value to the development of policy, education, and interventions.
ABSTRACT
Background: Substantial COVID-19 research investment has been allocated to randomized clinical trials (RCTs) on hydroxychloroquine/chloroquine, which currently face recruitment challenges or early discontinuation. We aimed to estimate the effects of hydroxychloroquine and chloroquine on survival in COVID-19 from all currently available RCT evidence, published and unpublished. Methods: Rapid meta-analysis of ongoing, completed, or discontinued RCTs on hydroxychloroquine or chloroquine treatment for any COVID-19 patients (protocol: https://osf.io/QESV4/). We systematically identified published and unpublished RCTs by September 14, 2020 (ClinicalTrials.gov, WHO International Clinical Trials Registry Platform, PubMed, Cochrane COVID-19 registry). All-cause mortality was extracted (publications/preprints) or requested from investigators and combined in random-effects meta-analyses, calculating odds ratios (ORs) with 95% confidence intervals (CIs), separately for hydroxychloroquine/chloroquine. Prespecified subgroup analyses included patient setting, diagnostic confirmation, control type, and publication status. Results: Sixty-two trials were potentially eligible. We included 16 unpublished trials (1596 patients) and 10 publications/preprints (6317 patients). The combined summary OR on all-cause mortality for hydroxychloroquine was 1.08 (95%CI: 0.99, 1.18; I-square=0%; 24 trials; 7659 patients) and for chloroquine 1.77 (95%CI: 0.15, 21.13, I-square=0%; 4 trials; 307 patients). We identified no subgroup effects. Conclusions: We found no benefit of hydroxychloroquine or chloroquine on the survival of COVID-19 patients. For hydroxychloroquine, the confidence interval is compatible with increased mortality (OR 1.18) or negligibly reduced mortality (OR 0.99). Findings have unclear generalizability to outpatients, children, pregnant women, and people with comorbidities.