Mandatory data and code sharing for research published by The BMJ

BMJ, Journal Year: 2024, Volume and Issue: unknown, P. q324 - q324

Published: March 5, 2024

Language: Английский

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A commitment to act on data sharing

BMJ, Journal Year: 2023, Volume and Issue: unknown, P. p1609 - p1609

Published: July 13, 2023

The argument is simple enough.Ensuring that research registered in advance, the findings reported quickly, and data code shared readily best interests of science public good.Ultimately, pays for enterprise, scientific community must be held accountable.But nothing involves commercial interests, academic rivalry, political agendas, perverse incentives publishing ever simple.What obvious, such as importance sharing from research, rapidly becomes complex insoluble (

Language: Английский

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Current policies of non‐commercial funders towards transparency in clinical trials

European Journal of Clinical Investigation, Journal Year: 2024, Volume and Issue: 54(6)

Published: Feb. 24, 2024

None. Data S1. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by authors. Any queries (other than missing content) should be directed to corresponding author article.

Language: Английский

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Design, cohort profile and comparison of the KTD-Innov study: a prospective multidimensional biomarker validation study in kidney allograft rejection

European Journal of Epidemiology, Journal Year: 2024, Volume and Issue: 39(5), P. 549 - 564

Published: April 16, 2024

Language: Английский

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COVID-19-related research data availability and quality according to the FAIR principles: A meta-research study

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Nov. 15, 2023

Abstract Background As per the FAIR principles (Findable, Accessible, Interoperable, and Reusable), scientific research data should be findable, accessible, interoperable, reusable. The COVID-19 pandemic has led to massive activities an unprecedented number of topical publications in a short time. There not been any evaluation assess if this COVID-19-related complied with (or FAIRness) so far. Objective Our objective was investigate availability open compliance FAIRness. Methods We conducted comprehensive search retrieved all open-access articles related from journals indexed PubMed, available Europe PubMed Central database, published January 2020 through June 2023, using metareadr package. Using rtransparent , validated automated tool, we identified that included link their raw hosted public repository. then screened those repositories which specifically for pertaining paper. Subsequently, automatically assessed adherence FAIRsFAIR Research Data Object Assessment Service (F-UJI) rfuji scores ranged 1–22 had four components. reported descriptive analysis each article type, journal category used linear regression models find most influential factors on FAIRness data. Results 5,700 URLs were final analysis, sharing general-purpose mean (standard deviation, SD) level metrics 9.4 (4.88). percentages moderate or advanced as follows: Findability: 100.0%, Accessibility: 21.5%, Interoperability: 46.7%, Reusability: 61.3%. overall component-wise monthly trends consistent over follow-up. Reviews (9.80, SD=5.06, n=160), dental (13.67, SD=3.51, n=3) Harvard Dataverse (15.79, SD=3.65, n=244) highest scores, whereas letters (7.83, SD=4.30, n=55), neuroscience (8.16, SD=3.73, n=63), deposited GitHub (4.50, SD=0.13, n=2,152) showed lowest scores. Regression factor repository (R 2 =0.809). Conclusion This paper underscored potential improvement across facets principles, specific emphasis enhancing Interoperability Reusability shared within general during pandemic.

Language: Английский

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A data-driven approach to choosing privacy parameters for clinical trial data sharing under differential privacy

Journal of the American Medical Informatics Association, Journal Year: 2024, Volume and Issue: 31(5), P. 1135 - 1143

Published: March 8, 2024

Clinical trial data sharing is crucial for promoting transparency and collaborative efforts in medical research. Differential privacy (DP) a formal statistical technique anonymizing shared that balances of individual records accuracy replicated results through "privacy budget" parameter, ε. DP considered the state art privacy-protected publication underutilized clinical sharing. This study focused on identifying ε values data.

Language: Английский

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The role of programming code sharing in improving the transparency of medical research

BMJ, Journal Year: 2023, Volume and Issue: unknown, P. p2402 - p2402

Published: Oct. 17, 2023

Language: Английский

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Improving Reproducibility in Epidemiology

Springer eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 22

Published: Jan. 1, 2024

Language: Английский

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SHARE: An ethical framework for equitable data sharing in Caribbean health research

Revista Panamericana de Salud Pública, Journal Year: 2024, Volume and Issue: 48, P. 1 - 1

Published: Dec. 16, 2024

Data sharing increasingly underpins collaborative research to address complex regional and global public health problems. Advances in analytic tools, including machine learning, have expanded the potential benefits derived from large repositories of open data. Participating data collaboratives offers opportunities for Caribbean researchers advance region's population through shared data-driven science policy. However, ethical challenges complicate these efforts. Here we discuss fundamental that threaten impede progress if not strategically addressed, power dynamics among funders high-income countries stakeholders; equity; threats privacy; risk stigma. These may be exacerbated by resource infrastructure limitations often seen small island developing states (SIDS) low- middle-income countries. We propose a framework

Language: Английский

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Breaking the silence of sharing data in medical research

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(5), P. e0301917 - e0301917

Published: May 29, 2024

Data sharing is highly advocated in the scientific community, with numerous organizations, funding agencies, and journals promoting transparency collaboration. However, limited research exists on actual data practices. We conducted a comprehensive analysis of intent to share individual participant (IPD) total 313,990 studies encompassing clinical trials observational obtained from ClinicalTrials.gov, spanning period 2000 2023. Our study found that only 10.3% principal investigators (PIs) expressed IPD. Clinical were more likely than (odds ratio, OR = 1.98, 95% CI: 1.92–2.04). Large sample size 1.69 times small ones (95% 1.65–1.73). Studies registered after 2018 1.6 1.57–1.64) before 2019. NIH other US Federal agency-funded had 1.49 higher odds 1.43–1.55) funders. USA-based 1.53 1.49–1.57) out USA. Biological 1.58 drug 1.51–1.66). Phase III highest odds, 2.47 times, 2.38–2.56) non-Phase trials.

Language: Английский

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