Science depends on good data. Data are central to our understanding of the natural world, yet most data in ecology and evolution are lost to science – except perhaps in summary form – very quickly after they are collected. Once the results of a study are published, the data on which those results are based are often stored unreliably, subject to loss by hard drive failure and (even more likely) by the researcher forgetting the specific details required to use the data (Michener et al., 1997). Moreover, most data are never available to the broader community, even after publication of the results; in most cases, this unavailability becomes permanent following the eventual death of the researchers involved. In evolutionary biology, we are losing nearly all of an important legacy.
Yet evolutionary data, even after the main results for which they were collected are published, are invaluable to science, for meta-analysis, new uses and quality control. With the increasing use of meta-analysis to summarize multiple studies, it has become clear that necessary summary statistics are often not published. In many cases, a study can only be used if the original data are available to the meta-analysts. Furthermore, data often can be used in ways beyond the questions that sparked its collection. There is an increasing realization that long-term data are needed to understand the rapid changes we see today and that these data may well come from studies conducted years ago for a different purpose. For example, many studies contain information that can serve later as a baseline for detecting population trends, even decades later. The availability of data from published studies also allows error checking, making science more open and letting us more rapidly reach accurate conclusions. Finally, articles that have had data archived are more useful to – and more cited by – other scientists. A study of articles that report microarray data found that articles that archived their data were cited 69% more often than articles that did not archive (Piwowar et al., 2007).
Data that are properly archived are saved for posterity. Archives also function to preserve data in a useable form for the original authors. Moreover, if data sets are put into a readily interpretable format while the methods and structure of the data are foremost in the scientists’ minds, those data can be used later more easily by those scientists and others.
The example of GenBank shows the value of the availability of data for all of these reasons. The modern synthetic use of DNA sequence data would not be possible without the near-universal use of GenBank as a public archive. Moreover, GenBank would not be nearly as complete as it is without the communal decision to archive all DNA sequence data, a decision initially introduced by journals.
To promote the preservation and fuller use of data, the Journal of Evolutionary Biology along with other key journals in evolution (The American Naturalist, Evolution, Molecular Ecology, Heredity) is introducing a new data archiving policy enacted by the Councils of the societies owning or sponsoring these journals. For example, the policy of the Journal of Evolutionary Biology will state:
The Journal of Evolutionary Biology requires, as a condition for publication, that data supporting the results in the paper should be archived in an appropriate public archive, such as GenBank, TreeBASE, Dryad, the Knowledge Network for Biocomplexity or other suitable long-term and stable public repositories. Data are important products of the scientific enterprise, and they should be preserved and usable for decades in the future. Authors may elect to have the data publicly available at time of publication, or, if the technology of the archive allows, may opt to embargo access to the data for a period up to a year after publication. Exceptions may be granted at the discretion of the editor, especially for sensitive information such as human subject data or the location of endangered species.
JEB has required the deposition of data in public archives since 1999 (see “Additional Material” section in instructions to authors). What has now changed is the increase in the diversity of archives that are available. Data that have an established standard repository, such as DNA sequences, should continue to be archived in the appropriate repository, such as GenBank. For more idiosyncratic data, the data can be placed in a more flexible digital data library such as the NSF-sponsored Dryad archive at datadryad.org. It is possible that a single study may have data in more than one archive. We continue to encourage the publication of accession numbers in the relevant manuscript.
When the policy is fully in place, authors will archive the data required to support the conclusions in their published article, along with sufficient details that a third party can reasonably interpret those data correctly. In most cases this will require a short additional text document, with details specifying the meaning of each column in the data set. The preparation of such shareable data sets will be easiest if these files are prepared as part of the data analysis phase of the preparation of the article, rather than after acceptance of a manuscript.
The data should be saved usually at the individual level, although what is most important is that the data be saved in a way that makes the most sense for later usability. Summary statistics (like means and standard deviations) are not sufficient, because it would not be enough information for later analysis. At the same time, data in their most raw form, such as videotapes, field notebooks or sequencing trace files are not required. For example, if a study used videotape to determine the time required for animals to make a choice in t-maze, the data should be recorded with the time for each subject.
The data archiving policy is designed to address several concerns that some researchers may have about data sharing. To protect the ability of individual researchers to use the data that they have collected, the policy allows an embargo period after publication. Although the data will be entered into an archive at the time of publication, the data may be restricted from public view for up to a year. This allows the original researcher time to publish other articles based on the data set. The policy also allows longer embargo periods at the discretion of the editor in exceptional cases. In addition, the requirement is only for data that have already been used in the publication in question; other data from the same research project that have not yet been described in a publication need not be archived. Finally, data that are particularly sensitive, such as location information for endangered species subject to poaching, should not be archived in a publicly accessible format. Human subject data should be anonymized (see the recommendations of the National Human Subjects Protection Advisory Committee, 2002).
Throughout the history of evolutionary studies, enormous quantities of valuable data have been lost to future science, for a variety of technical and cultural reasons. The true value of these data was thus never realized. There are no longer any meaningful technical barriers to long-term storage, and just as in the case of DNA sequence data, it is time for the culture of our shared use of data to evolve. With this general data policy, we think that science will reap great benefits for generations to come and that the growth and importance of research in evolutionary biology will be facilitated.