Prepublication data sharing: the Toronto statement
Sarah Tomlin
Wednesday, 02 September 2009 20:39 UTC
Sharing knowledge is key to the progress of science, but researchers do not always release data and research materials, even after publication. Earlier this year, two research communities held meetings with a broad range of stakeholders to discuss ways to promote data sharing in biology, and they report their recommendations in two Opinion articles in this week’s Nature. See special issue on data sharing here.
Data producers and users met at a workshop in Toronto in May to discuss the benefits and best practices of rapid data release prior to publication. Ewan Birney, Tom Hudson and colleagues report the main conclusions of these discussions in a community statement, free to access here.
The Toronto group propose that the principles for early release of genomics data should be extended to other large datasets in biology and medicine. A grace period should be allowed, if requested, to enable data producers to analyse and publish their dataset, but this should be limited to one year. The authors also suggest a set of best practices for funding agencies, scientists and journal editors.
The recommendations are intended to spark community discussion on this subject. Ewan Birney, Tom Hudson and others will be responding to reader comments in this forum. Be sure to have your say.
Updated 09 September 2009 17:06 UTC
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I should clarify that I am not underestimating the profile of the scientist who manages to handle the data statistically, otherwise is necessary.
But for science to advance it is necessary that there exist people who be creative, this enhances the vitality of the investigation.
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“Fear of being scooped” could be abrogated by a more equitable system of giving credit to contributors. In a more ideal world, if someone else used your data in a publication, you would still get proper credit for it. With electronic publication becoming more prevalent, creating such a system seems possible to implement. I’m sure people are working on this.
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I agree that fair attribution to those who put in intellectual effort to create a data set is essential. Data publication should be given the same recognition as results publication. To that end, the International Polar Year has developed data citation guidelines in keeping with the IPY Data Policy’s call for fair attribution. These guidelines are not unique and correspond to similar efforts in other communities. The guidelines are available at http://ipydis.org/data/citations.html.
Now journals and reviewers need to ensure that data citation is a normal and expected process in publication.
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Dear all: After submission of the Toronto Statement, I was provided a link to
an excellent success story in data sharing. It’s the Alzheimers Disease Neuroimaging Initiative..“http://www.loni.ucla.edu/ADNI/”
It’s a multi center study with the data protocols carefully defined and monitored for consistency across sites. It includes clinical exam, CSF, blood, biopsy, and a number of brain imaging scans on every patient.
The data is deposited centrally in near real time. It is quaranteened for a short period (less than 30 days) purely for QA. There are no publication embargoes or limits on what you can do or when you can publish.“http://www.loni.ucla.edu/ADNI/Data/ADNI_%20DPC_Policy.pdf”
I am impressed by this site and think that it is worthwhile sharing with others.
Tom
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Both the generator and reviewer of an innovative idea as it provides data and analysis should have the same privileges as authors in a publication. Is what I think.
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Sorry, both the generator,reviewer and traductor of an innovative idea and the scientist that provides data and analysis should have the same privileges how author in a publication. Is what I think.
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Talking data sharing is far from actually practicing it. One needs to be open-minded for this. Different individuals can have a different perspective of looking at a biological phenomenon. Scientist should collaborate to form bigger and more precise projects, rather than replicating the experiments. I work on phyto-pharmacology in metabolic syndrome and I am ready to share my understanding in pharmacology, diabetes, obesity. Any takers are welcome. greetings
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Many kinds of biological data include parameters for location (of a sample organism, for example) or area (of a migration path, for example). Software interface and encoding standards (mainly from the Open Geospatial Consortium) that enable efficient publication, discovery, assessment and use of geospatial data (and management of geolocated sensors) are available and coming into wide use in areas such as ocean observation and meteorology. Biologists with geospatial data ought to follow the oceanographers’ and meteorologists’ example. Only if we share data about the animate and inanimate features and phenomena of our one Earth can we understand the complex relationships that support our precarious existence.
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