2017年6月英语六级仔细阅读1题源文章

　　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').

　　Box 1: Abundant options

　　“Lots of people are getting into data-hosting, and I think it will be tricky to decide where to put your data,” says Heather Piwowar, who studies data-sharing for the US National Evolutionary Synthesis Center in Durham, North Carolina.

　　Share and share alike

　　Although exhortations to share data often concentrate on the moral advantages of sharing, the practice is not purely altruistic. Researchers who share get plenty of personal benefits, including more connections with colleagues, improved visibility and increased citations. The most successful sharers — those whose data are downloaded and cited the most often — get noticed, and their work gets used. For example, one of the most popular data sets on multidisciplinary repository Dryad is about wood density around the world; it has been downloaded 5,700 times. Co-author Amy Zanne, a biologist at George Washington University in Washington DC, thinks that users probably range from climate-change researchers wanting to estimate how much carbon is stored in biomass, to foresters looking for information on different grades of timber. “I would much prefer to have my data used by the maximum number of people to ask their own questions,” she says. “It's important to allow readers and reviewers to see exactly how you arrive at your results. Publishing data and code allows your science to be reproducible.”