Open data-sharers are still in the minority in many fields. Although many researchers broadly agree that public access to raw data would accelerate science — because other scientists might be able to make advances not foreseen by the data's producers — most are reluctant to post the results of their own labours online (see Nature 461, 160–163; 2009). When Wolkovich, for instance, went hunting for the data from the 50 studies in her meta-analysis, only 8 data sets were available online, and many of the researchers whom she e-mailed refused to share their work. Forced to extract data from tables or figures in publications, Wolkovich's team could conduct only limited analyses.

Some communities have agreed to share online — geneticists, for example, post DNA sequences at the GenBank repository, and astronomers are accustomed to accessing images of galaxies and stars from, say, the Sloan Digital Sky Survey, a telescope that has observed some 500 million objects — but these remain the exception, not the rule. Historically, scientists have objected to sharing for many reasons: it is a lot of work; until recently, good databases did not exist; grant funders were not pushing for sharing; it has been difficult to agree on standards for formatting data and the contextual information called metadata; and there is no agreed way to assign credit for data.

But the barriers are disappearing, in part because journals and funding agencies worldwide are encouraging scientists to make their data public. Last year, the Royal Society in London said in its report Science as an Open Enterprise that scientists need to “shift away from a research culture where data is viewed as a private preserve”. Funding agencies note that data paid for with public money should be public information, and the scientific community is recognizing that data can now be shared digitally in ways that were not possible before. To match the growing demand, services are springing up to make it easier to publish research products online and enable other researchers to discover and cite them. There are so many, in fact, that choosing where and how to publish data sets and other supplementary material can be confusing (see 'Abundant options').

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