Journal of Bone and Joint Surgery, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 18, 2024
Jupiter, Jesse B.; Regazzoni, Pietro; Liu, Wen-Chih; Dell'Oca, Alberto Fernandez Author Information
Language: Английский
Journal of Bone and Joint Surgery, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 18, 2024
Jupiter, Jesse B.; Regazzoni, Pietro; Liu, Wen-Chih; Dell'Oca, Alberto Fernandez Author Information
Language: Английский
BMJ, Journal Year: 2024, Volume and Issue: unknown, P. q324 - q324
Published: March 5, 2024
Language: Английский
Citations
12BMJ, 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
Citations
12European 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
Citations
2European Journal of Epidemiology, Journal Year: 2024, Volume and Issue: 39(5), P. 549 - 564
Published: April 16, 2024
Language: Английский
Citations
2bioRxiv (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
Citations
4Journal 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
Citations
1BMJ, Journal Year: 2023, Volume and Issue: unknown, P. p2402 - p2402
Published: Oct. 17, 2023
Language: Английский
Citations
1Springer eBooks, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 22
Published: Jan. 1, 2024
Language: Английский
Citations
0Revista 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
Citations
0PLoS 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
Citations
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