Archive for the ‘Data availability’ Category

We are delighted to announce the launch of a new partnership with The Company of Biologists to support their authors in making the data underlying their research available to the community.

COBNewLogo300dpiThe Company of Biologists is a not-for-profit publishing organization dedicated to supporting and inspiring the biological community. The Company publishes five specialist peer-reviewed journals:

The Company of Biologists offers further support to the biological community by facilitating scientific meetings, providing travel grants for researchers and supporting research societies.

Manuscript submission for all COB journals is now integrated with data submission to Dryad, meaning COB authors can conveniently submit their data packages and manuscripts at the same time. Dryad then makes the data securely available to journal reviewers, and releases them to the public if/when the paper is published.

We congratulate The Company of Biologists on taking this important step to help facilitate open data. To learn more about how your organization or journal can partner with Dryad, please contact us.

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Our latest featured data package is from Alexandra Swanson and colleagues at the Snapshot Serengeti project, and accompanies their peer-reviewed article in Scientific Data.  It provides a unique resource for studying one of the world’s most extraordinary mammal assemblages and also for studies of computer vision and machine learning. In addition, data from Snapshot Serengeti is already being used in biology and computer science classrooms to enable students to work on solving real problems with authentic research data.


Snapshot Serengeti, CC BY-NC-SA 3.0

The raw data (which are being made available from the University of Minnesota Supercomputing Institute) consist of 1.2 million sets of images collected between February 2011 and May 2013 from 225 heat and motion triggered cameras, operating day and night, distributed over 1,135 sq. km. in Serengeti National Park in Tanzania.  This staggering trove of images was classified by 28,040 registered and ~40,000 unregistered volunteers on Snapshot Serengeti (a Zooniverse project) according to the species present (if any), the number of individuals, the presence of young, and what behaviors were being displayed, such as standing, resting, moving, eating, or interacting.

Remarkably, this vast army of citizen scientists was classifying the images faster than they were being produced, and each image set was classified on average by nine different volunteers.  This led to consensus classifications with high accuracy, 96.6% for species identifications relative to an expert-classified gold set.  Of the more than 300,000 image sets that contain animals, 48 different species were seen, including rare mammals such as the aardwolf and the zorilla.


zorilla (image from Snapshot Serengeti CC BY-NC-SA 3.0)

The Dryad data package includes the classifications from all the individual volunteers, the consensus classifications, information about when each camera was operational, and the expert classification of 4,149 image sets as a gold standard.


  • Swanson et al. (2015) Snapshot Serengeti, high frequency annotated camera trap images of 40 mammalian species in an African savannah. Scientific Data.  http://dx.doi.org/10.1038/sdata.2015.26
  • Swanson et al. (2015) Data from: Snapshot Serengeti, high frequency annotated camera trap images of 40 mammalian species in an African savannah. Dryad Digital Repository http://doi.org/10.5061/dryad.5pt92

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The reason why Dryad is in the business of archiving, preserving, and providing access to research data is so that it will be reused, whether for deeper reading of the publication, for post-publication review, for education, or for future research. While it’s not yet as easy as we would like to track data reuse, one metric that is straightforward to collect is the number of times a dataset has been downloaded, and this is one of two data reuse statistics reported by our friends at ImpactStory and Plum Analytics.

2014 with fireworks

The numbers are very encouraging. There are already over a quarter million downloads for the 8,897 data files released in 2014 (from 2,714 data packages). That’s over 28 downloads per data file. While there is always the caveat that some downloads may be due to activity from newly emerged bots that we have yet to recognize and filter out, we think it is safe to say that most of these downloads are from people.

To celebrate, we would like to pay special tribute to the top five data packages from 2014, as measured by the maximum number of downloads for any single file (since many data packages have more than one) at the time of writing. They cover a diversity of topics from livestock farming in the Paleolithic to phylogenetic relationships among insects. That said, we are struck by the impressively strong showing for plant science — 3 of the top 5 data packages.

In 5th place, with 453 downloads

In 4th place, with 581 downloads

In 3rd place, with 626 downloads

In 2nd place, with 4,672 downloads

And in 1st place, with a staggering 34,879 downloads

Remarkably, given the number of downloads, this last data package was only released in November.

We’d like to thank all of our users, whether you contribute data or reuse it (or both), for helping make science just a little more transparent, efficient, and robust this past year. And we are looking forward to finding out some more of what you did with all those downloads in 2015!





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Dryad has been proud to support integrated data and manuscript submission for PLOS Biology since 2012, and for PLOS Genetics since 2013.  Yet there are over 400 data packages in Dryad from six difFeatured imageferent PLOS journals in addition to two research areas of PLOS Currents. Today, we are pleased to announce that we have expanded submission integration to cover all seven PLOS journals, including the two above plus PLOS Computational BiologyPLOS MedicinePLOS Neglected Tropical DiseasesPLOS ONE, and PLOS Pathogens.  

PLOS received a great deal of attention when they modified their Data Policy in March providing more guidance to authors on how and where to make their data available and introducing Data Availability Statements. Dryad’s integration process has been enhanced in a few ways to support this policy and also the needs of a megajournal like PLOS ONE.  We believe these modifications provide an attractive model for integration that other journals may wish to follow. The key difference for authors who wish to deposit data in Dryad is that you are now asked to deposit your data before submitting your manuscript.

  1. PLOS authors are now asked to provide a Data Availability Statement during initial manuscript submission, as shown in the screenshot below. There is evidence that introducing a Data Availability Statement greatly reinforces the effectiveness of a mandatory data archiving policy, and so we expect this change will substantially increase the availability of data for PLOS publications.  PLOS authors using Dryad are encouraged to provide the provisional Dryad DOI as part of the Data Availability Statement.
  2. PLOS authors are now also asked to provide a Data Review URL where reviewers can access the data, as shown in the second screenshot. While Dryad has offered secure, anonymous reviewer access for some time, the difference now is that PLOS authors using Dryad will be able to enter the Data Review URL  at the time of initial manuscript submission.
  3. In addition to these visible changes, we have also introduced an Application Programming Interface (API) to facilitate behind-the-scenes metadata exchange between the journal and the repository, making the process more reliable and scalable. This was critical for PLOS ONE, which published 31,500 articles in 2013.  Use of this API is now available as an integration option to all journals as an alternative to the existing email-based process, which we will continue to support.

PLOS Data Availability Statement interface

PLOS Data Review URL interface

The manuscript submission interface for PLOS now includes fields for a Data Availability Statement and a Data Review URL.

If you are planning to submit a manuscript but are unsure about the Dryad integration options or process for your journal, just consult this page. For all PLOS journals, the data are released by Dryad upon publication of the article.  Should the manuscript be rejected, the data files return to the author’s private workspace and the provisional DOI is not registered.  Authors are responsible for paying Data Publication Charges only if and when their manuscript is accepted.

Jennifer Lin from PLOS and Carly Strasser from the California Digital Library recently offered a set of community recommendations for ways that publishers could promote better access to research data:

  • Establish and enforce a mandatory data availability policy.
  • Contribute to establishing community standards for data management and sharing.
  • Contribute to establishing community standards for data preservation in trusted repositories.
  • Provide formal channels to share data.
  • Work with repositories to streamline data submission.
  • Require appropriate citation to all data associated with a publication—both produced and used.
  • Develop and report indicators that will support data as a first-class scholarly output.
  • Incentivize data sharing by promoting the value of data sharing.

Today’s expanded and enhanced integration with Dryad, which inaugurates the new Data Repository Integration Partner Program at PLOS, is an excellent illustration of how to put these recommendations into action.

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The following is a guest post from Tom Jefferson of The Cochrane Collaboration, Peter Doshi of the University of Maryland and Carl Heneghan from the University of Oxford. We asked them to tell the story behind their recent Cochrane systematic review [1] and dataset in Dryad [2] which holds valuable lessons about the evidence-base on which major public health recommendations are decided.  -TJV1918 Influenza Poster

In the late 2000s, half the world was busy buying and stockpiling the neuraminidase inhibitors oseltamivir (Tamiflu, Roche) and zanamivir (Relenza, GSK) in fear of an influenza pandemic.

The advice to stockpile for a pandemic and also use the drugs in non-pandemic, seasonal influenza seasons came from such august bodies as the World Health Organization (WHO), the US Centers for Disease Control and Prevention (CDC) and its European counterpart, the ECDC. However, they were stockpiling on the basis of an unclear rationale, mixing the effect of the antiviral drugs on the complications of influenza (mainly pneumonia and hospitalizations) and their capacity to slow down viral spread giving time for vaccines to be crash produced and deployed.

It has since become clear that none of these parties had seen all the clinical trial evidence for these drugs. They had based their recommendations on reviews of “the literature” which sounds impressive, but in fact refers to short trial reports published in journal articles rather than the underlying detailed raw data. For example, key assumptions of antiviral performance found in the US national pandemic plan trace back to a six page long journal article written by Roche which reported on a pooled-analysis of 10 randomized trials of which only 2 have ever been published.

In contrast, each of the corresponding internal clinical study reports for these 10 trials runs thousands of pages (for background on what clinical study reports are, see here.) Despite the stockpiling, these reports have never been reviewed by CDC, ECDC, or WHO. The WHO and CDC both refused to answer our questions on the evidence base for their policies.

Our Cochrane systematic review of neuraminidase inhibitors, funded by the National Institute for Health Research in the UK, was based on analysis of the full clinical study reports for these drugs, not short journal publications. We obtained these reports from the European Medicines Agency, Roche, and GlaxoSmithKline.  It took us nearly four years to obtain the full set of reports. The story of how we got hold of the complete set of clinical trials with no access restrictions is told in our essay “Multisystem failure: the story of anti-influenza drugs”.

With the publication of our review, we are making all 107 full clinical study reports publicly available. If you disagree with our findings, if you want to carry out your own analysis or if you are just curious to see what around 150,000 pages of data look like, they are one click away. Now the discussion about how well these drugs work can happen with all parties able to independently analyze all the trial evidence. This is called open science.

Be aware that there are some minimal redactions carried out by GSK and Roche. They did this to protect investigator and participant identity. While protecting participant identity is understandable, the EMA carries a different view towards protecting investigator identity: “names of experts or designated personnel with legally defined responsibilities and roles with respect to aspects of the Marketing Authorisation dossier (e.g. QP, QPPV, Clinical expert, Investigator) are included in the dossier because they have a legally defined role or responsibility and it is in the public interest to release this data”.


  1. Jefferson T, Jones MA, Doshi P, Del Mar CB, Hama R, Thompson MJ, Spencer EA, Onakpoya I, Mahtani KR, Nunan D, Howick J, Heneghan CJ (2014) Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane Database of Systematic Reviews, online in advance of print. doi:10.1002/14651858.CD008965.pub4
  2. Jefferson T, Jones MA, Doshi P, Del Mar CB, Hama R, Thompson MJ, Spencer EA, Onakpoya I, Mahtani KR, Nunan D, Howick J, Heneghan CJ (2014) Data from: Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Dryad Digital Repository. doi:10.5061/dryad.77471

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We are delighted to announce the availability of the data underlying the book “40 Years of EvGrant 40yrs of evol cover copyolution” by Peter and Rosemary Grant. In this new book, the Grants give an account of their classic, long-term study of Darwin’s finches on one of the Galápagos Islands.  From the announcement by Princeton University Press.

The authors used a vast and unparalleled range of ecological, behavioral, and genetic data–including song recordings, DNA analyses, and feeding and breeding behavior–to measure changes in finch populations on the small island of Daphne Major in the Galápagos archipelago. They find that natural selection happens repeatedly, that finches hybridize and exchange genes rarely, and that they compete for scarce food in times of drought, with the remarkable result that the finch populations today differ significantly in average beak size and shape from those of forty years ago. The authors’ most spectacular discovery is the initiation and establishment of a new lineage that now behaves as a new species, differing from others in size, song, and other characteristics. The authors emphasize the immeasurable value of continuous long-term studies of natural populations and of critical opportunities for detecting and understanding rare but significant events.

“40 Years of Evolution”, which is written a style that will be accessible to researchers, students and a more general audience, includes over 100 line drawings illustrating quantitative patterns among the many variables the authors have studied. There are 82 data files being made available in Dryad for researchers and students to explore the numbers behind those figures.  We are proud to be the custodians of this unique scientific resource.

For students and teachers interested in the Grants’ long-term studies of Darwin’s Finches, we also recommend the excellent background material and hands-on data analysis activities from the HHMI BioInteractive site.

Data citation: Grant PR, Grant BR (2013) Data from: 40 years of evolution. Darwin’s finches on Daphne Major Island. Dryad Digital Repository. http://dx.doi.org/10.5061/dryad.g6g3h


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The Data Citation Synthesis Group has released a draft Declaration of Data Citation Principles and invites comment.

This has been a very interesting and positive collaborative process and has involved a number of groups and committed individuals. Encouraging the practice of data citation, it seems to me, is one of the key steps towards giving research data its proper place in the literature.

As the preamble to the draft principles states:

Sound, reproducible scholarship rests upon a foundation of robust, accessible data. For this to be so in practice as well as theory, data must be accorded due importance in the practice of scholarship and in the enduring scholarly record. In other words, data should be considered legitimate, citable products of research. Data citation, like the citation of other evidence and sources, is good research practice.

In support of this assertion, and to encourage good practice, we offer a set of guiding principles for data citation.

Please do comment on these principles. We hope that with community feedback and support, a finalised set of principles can be widely endorsed and adopted.

Discussion on a variety of lists is welcome, of course. However, if you want the Synthesis Group to take full account of your views, please be sure to post your comments on the discussion forum.

Some notes and observations on the background to these principles

I would like to add here some notes and observations on the genesis of these principles. As has been widely observed there have been a number of groups and interested parties involved in exploring the principles of data citation for a number of years. Mentioning only some of the sources and events that affected my own thinking on the matter, there was the 2007 Micah Altman and Gary King article, in DLib, which offered ‘A Proposed Standard for the Scholarly Citation of Quantitative Data’ and Toby Green’s OECD White Paper ‘We need publishing standards for datasets and data tables’ in 2009. Micah Altman and Mercè Crosas organised a workshop at Harvard in May 2011 on Data Citation Principles. Later the same year, the UK Digital Curation Centre published a guide to citing data in 2011.

The CODATA-ICSTI Task Group on Data Citation Standards and Practices (co-chaired by Christine Borgman, Jan Brase and Sara Callaghan) has been in existence since 2010. In collaboration with the US National CODATA Committee and the Board on Research Data and Information, a major workshop was organised in August 2011, which was reported in ‘For Attribution: Developing Data Attribution and Citation Practices and Standards’.

The CODATA-ICSTI Task Group then started work on a report covering data citation principles, eventually entitled ‘Out of Cite, Out of Mind’ – drafts were circulated for comment in April 2013 and the final report was released in September 2013.

Following the first ‘Beyond the PDF’ meeting in Jan 2011 participants produced the Force11 Manifesto ‘Improving Future Research Communication and e-Scholarship’ which places considerable weight on the availability of research data and the citation of those data in the literature. At ‘Beyond the PDF II’ in Amsterdam, March 2013, a group comprising Mercè Crosas, Todd Carpenter, David Shotton and Christine Borgman produced ‘The Amsterdam Manifesto on Data Citation Principles’. In the very same week, in Gothenburg, an RDA Birds of a Feather group was discussing the more specific problem of how to support, technologically, the reliable and efficient citation of dynamically changing or growing datasets and subsets thereof. And the broader issues of the place of data and research publication were being considered in the ICSU World Data Service Working Group on Data Publication. This group has, in turn, formed the basis for an RDA Interest Group.  Oooffff!

How great a thing is collaboration?

From June 2013, as the Force11 Group was preparing its website and activities to take forward the work on the Amsterdam Manifesto, calls came in from a number of sources for these various groups and initiatives to coordinate and collaborate. This was admirably well-received and from July the ‘Data Citation Synthesis Group’ had come into being with an agreed mission statement:

The data citation synthesis group is a cross-team committee leveraging the perspectives from the various existing initiatives working on data citation to produce a consolidated set of data citation principles (based on the Amsterdam Manifesto, the CODATA and other sets of principles provided by others) in order to encourage broad adoption of a consistent policy for data citation across disciplines and venues. The synthesis group will review existing efforts and make a set of recommendations that will be put up for endorsement by the organizations represented by this synthesis group.

The synthesis group will produce a set of principles, illustrated with working examples, and a plan for dissemination and distribution. This group will not be producing detailed specifications for implementation, nor focus on technologies or tools.

As has been noted elsewhere , the group comprised 40 individuals and brought together a large number of organisations and initiatives. What followed over the summer was a set of weekly calls to discuss and align the principles. I must say, I thought these were admirably organised and benefitted considerably from participants’ efforts to prepare documents comparing the various groups’ statements. The face-to-face meeting of the group, in which a lot of detailed discussion to finalise the draft was undertaken, was hosted (with a funding contribution from CODATA) at the US National Academies of Science between the 2nd RDA Plenary and the DataCite Summer Meeting (which CODATA also co-sponsored). It has been intellectually stimulating and a real pleasure to contribute to these discussions and to witness so many informed and engaged people bashing out these issues.

The principles developed by the Synthesis Group are now open for comment and I urge as many people, researchers, editors and publishers as possible who believe that data has a place in scholarly communications to comment on them and, in due course, to endorse them and put them into practice.

Are we finally at the cusp of real change in practice? Will we now start seeing the practice of citing data sources become more and more widespread? It’s soon to say for sure, but I hope these principles, and the work on which they build, have got us to a stage where we can start really believing the change is well underway.

Simon Hodson is Executive Director of CODATA and a member of the Dryad Board of Directors.  This post was originally published on the CODATA blog.

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