ArticlePloS one2012
Mine, yours, ours? Sharing data on human genetic variation.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prevalence and predictors of data and code sharing in the medical and health sciences: systematic review with meta-analysis of individual participant data.BMJ (Clinical research ed.) · 2023Pooled it
- Open science interventions to improve reproducibility and replicability of research: a scoping review.Royal Society open science · 2025Article
- When are researchers willing to share their data? - Impacts of values and uncertainty on open data in academia.PloS one · 2020Article
- Multicenter data banking in management of dizzy patients: first results from the DizzyNet registry project.Journal of neurology · 2018Article
- To share or not to share? Expected pros and cons of data sharing in radiological research.European radiology · 2018Article
- Public availability of research data in dentistry journals indexed in Journal Citation Reports.Clinical oral investigations · 2018Article
- Observational
- Article
- Public Data Archiving in Ecology and Evolution: How Well Are We Doing?PLoS biology · 2015Article
- Biomedical Data Sharing and Reuse: Attitudes and Practices of Clinical and Scientific Research Staff.PloS one · 2015Article
- When data sharing gets close to 100%: what human paleogenetics can teach the open science movement.PloS one · 2015Article
- What drives academic data sharing?PloS one · 2015Article
- Article
- Why share data? Lessons learned from the fMRIDC.NeuroImage · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The achievement of a robust, effective and responsible form of data sharing is currently regarded as a priority for biological and bio-medical research. Empirical evaluations of data sharing may be regarded as an indispensable first step in the identification of critical aspects and the development of strategies aimed at increasing availability of research data for the scientific community as a whole. Research concerning human genetic variation represents a potential forerunner in the establishment of widespread sharing of primary datasets. However, no specific analysis has been conducted to date in order to ascertain whether the sharing of primary datasets is common-practice in this research field. To this aim, we analyzed a total of 543 mitochondrial and Y chromosomal datasets reported in 508 papers indexed in the Pubmed database from 2008 to 2011. A substantial portion of datasets (21.9%) was found to have been withheld, while neither strong editorial policies nor high impact factor proved to be effective in increasing the sharing rate beyond the current figure of 80.5%. Disaggregating datasets for research fields, we could observe a substantially lower sharing in medical than evolutionary and forensic genetics, more evident for whole mtDNA sequences (15.0% vs 99.6%). The low rate of positive responses to e-mail requests sent to corresponding authors of withheld datasets (28.6%) suggests that sharing should be regarded as a prerequisite for final paper acceptance, while making authors deposit their results in open online databases which provide data quality control seems to provide the best-practice standard. Finally, we estimated that 29.8% to 32.9% of total resources are used to generate withheld datasets, implying that an important portion of research funding does not produce shared knowledge. By making the scientific community and the public aware of this important aspect, we may help popularize a more effective culture of data sharing.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.