Vines et al. ask authors for the data underlying papers between 2 and 22 years old and find that the odds of it being reported extant decrease by 17% for every year since publication.

On Friday the 13th, I gave the morning keynote at the Online Northwest Conference  in Corvallis, OR. Thanks so much to the organization for ...

The Institute of Medicine takes a step in the right direction but we should move even faster  The Institute of Medicine (IOM), a venerable American institution that seeks to provide authoritative recommendations to decision makers and the public, released a report last month on Sharing Clinical Trial Data .1 The report is a welcome codification of guiding principles and frameworks. It reinforces many arguments for data sharing and urges that stakeholders “should foster a culture in which data sharing is the expected norm.”1 The IOM joins many other organizations, including drug companies,2 3 the European Medicines Agency,4 the National Institutes of Health,5 and the Bill and Melinda Gates Foundation,6 in making clear that study reporting and data sharing in medical research are imperative and the questions ahead are how, not whether.  The general support for data sharing in the IOM document will be familiar to The BMJ ’s readers, as this journal has long advocated the importance of transparency in scientific research and the need to report results and share data.7 The report provides what should be easily achievable recommendations for the research community. The committee called for data sharing only for new trials, though it urged consideration of sharing older studies. It stated that 18 months could elapse …

A list of trite and predictable excuses for not opening data, captured by Paul Suijkerbuijk and Ton Zijlstra

Background The widespread reluctance to share published research data is often hypothesized to be due to the authors' fear that reanalysis may expose errors in their work or may produce conclusions that contradict their own. However, these hypotheses have not previously been studied systematically.   Methods and Findings We related the reluctance to share research data for reanalysis to 1148 statistically significant results reported in 49 papers published in two major psychology journals. We found the reluctance to share data to be associated with weaker evidence (against the null hypothesis of no effect) and a higher prevalence of apparent errors in the reporting of statistical results. The unwillingness to share data was particularly clear when reporting errors had a bearing on statistical significance.   Conclusions Our findings on the basis of psychological papers suggest that statistical results are particularly hard to verify when reanalysis is more likely to lead to contrasting conclusions. This highlights the importance of establishing mandatory data archiving policies.

Competition and disorganization within their disciplines prevent many researchers from making their data publicly available, which is stunting scientific progress.

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Writing my post about AI and summoning the demon led me to re-read a number of articles on Cathy O'Neil's excellent mathbabe blog. I highlighted a point Cathy...

© The Author(s), 2014. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in BMC Research Notes 7 (2014): 79, doi:10.1186/1756-0500-7-79.

Very good section on how data gets swapped around between corps, government, and researchers.

Data-sharing is an essential tool for replication, validation and extension of empirical results. Using a hand-collected data set describing the data-…

Pete Binfield on OA, Carly Strasser on open data, Nicole Allen on OER in 2014.

Over the last decade, there have been significant changes in data sharing policies and in the data sharing environment faced by life science researchers. Using data from a 2013 survey of over 1600 life science researchers, we analyze the effects of sharing policies of funding agencies and journals. We also examine the effects of new sharing infrastructure and tools (i.e., third party repositories and online supplements). We find that recently enacted data sharing policies and new sharing infrastructure and tools have had a sizable effect on encouraging data sharing. In particular, third party repositories and online supplements as well as data sharing requirements of funding agencies, particularly the NIH and the National Human Genome Research Institute, were perceived by scientists to have had a large effect on facilitating data sharing. In addition, we found a high degree of compliance with these new policies, although noncompliance resulted in few formal or informal sanctions. Despite the overall effectiveness of data sharing policies, some significant gaps remain: about one third of grant reviewers placed no weight on data sharing plans in their reviews, and a similar percentage ignored the requirements of material transfer agreements. These patterns suggest that although most of these new policies have been effective, there is still room for policy improvement.

Changes clarify procedures for telling participants in NIH-funded studies how their data might be used.

Policy’s implementation is key to accelerating biomedical discoveries.