题目
题目 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， most are reluctant to post the results of their own labors online． Some communities have agreed to share online-geneticists， for example， post DNA sequences at the GenBank repository (库)， and astronomers are accustomed to accessing images of galaxies and stars from， say， the Sloan Digital Sky Survey， a telescope that has observed some 500million 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 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 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． Although calls to share data often concentrate on the moral advantages of sharing， the practice is not purely altruistic (利他的)． 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 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'd 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． " Even people whose data are less popular can benefit． By making the effort to organize and label files so others can understand them， scientists become more organized and better disciplined themselves， thus avoiding confusion later on． 32． What do many researchers generally accept？___ A． It is imperative (必要的) to protect scientists' patents． B． Repositories are essential to scientific research． C． Open data sharing is most important to medical science． D． Open data sharing is conducive (有利的) to scientific advancement． 33． According to the passage， what might hinder (阻碍) open data sharing？___ A． The fear of massive copying． B． The lack of a research culture． C． The belief that research data is private intellectual property． D． The concern that certain agencies may make a profit out of it． 34． What helps lift some of the barriers to open data sharing？___ A． The ever-growing demand for big data． B． The advancement of scientific technology． C． The changing attitude of journals and funders． D． The trend of social and economic development． 35． Dryad serves as an example to show how open data sharing___． A． is becoming increasingly popular B． benefits sharers and users alike C． makes researchers successful D． saves both money and labor
题目
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， most are reluctant to post the results of their own labors online．
Some communities have agreed to share online-geneticists， for example， post DNA sequences at the GenBank repository (库)， and astronomers are accustomed to accessing images of galaxies and stars from， say， the Sloan Digital Sky Survey， a telescope that has observed some 500million 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 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 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．
Although calls to share data often concentrate on the moral advantages of sharing， the practice is not purely altruistic (利他的)． 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 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'd 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． "
Even people whose data are less popular can benefit． By making the effort to organize and label files so others can understand them， scientists become more organized and better disciplined themselves， thus avoiding confusion later on．
32． What do many researchers generally accept？___
A． It is imperative (必要的) to protect scientists' patents．
B． Repositories are essential to scientific research．
C． Open data sharing is most important to medical science．
D． Open data sharing is conducive (有利的) to scientific advancement．
33． According to the passage， what might hinder (阻碍) open data sharing？___
A． The fear of massive copying．
B． The lack of a research culture．
C． The belief that research data is private intellectual property．
D． The concern that certain agencies may make a profit out of it．
34． What helps lift some of the barriers to open data sharing？___
A． The ever-growing demand for big data．
B． The advancement of scientific technology．
C． The changing attitude of journals and funders．
D． The trend of social and economic development．
35． Dryad serves as an example to show how open data sharing___．
A． is becoming increasingly popular
B． benefits sharers and users alike
C． makes researchers successful
D． saves both money and labor
Some communities have agreed to share online-geneticists， for example， post DNA sequences at the GenBank repository (库)， and astronomers are accustomed to accessing images of galaxies and stars from， say， the Sloan Digital Sky Survey， a telescope that has observed some 500million 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 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 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．
Although calls to share data often concentrate on the moral advantages of sharing， the practice is not purely altruistic (利他的)． 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 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'd 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． "
Even people whose data are less popular can benefit． By making the effort to organize and label files so others can understand them， scientists become more organized and better disciplined themselves， thus avoiding confusion later on．
32． What do many researchers generally accept？___
A． It is imperative (必要的) to protect scientists' patents．
B． Repositories are essential to scientific research．
C． Open data sharing is most important to medical science．
D． Open data sharing is conducive (有利的) to scientific advancement．
33． According to the passage， what might hinder (阻碍) open data sharing？___
A． The fear of massive copying．
B． The lack of a research culture．
C． The belief that research data is private intellectual property．
D． The concern that certain agencies may make a profit out of it．
34． What helps lift some of the barriers to open data sharing？___
A． The ever-growing demand for big data．
B． The advancement of scientific technology．
C． The changing attitude of journals and funders．
D． The trend of social and economic development．
35． Dryad serves as an example to show how open data sharing___．
A． is becoming increasingly popular
B． benefits sharers and users alike
C． makes researchers successful
D． saves both money and labor
题目解答
答案
32．D．细节理解题．根据第一段 Although many researchers broadly agree that public access to raw data would accelerate science， most are reluctant to post the results of their own labors online．尽管许多研究人员普遍认为公众获取原始数据会加速科学发展，但大多数人都不愿意在网上发布自己的工作成果．可知，许多研究人员普遍接受开放数据共享有利于科学进步．故选D．
33．C．细节理解题．根据第二段 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 there is no agreed way to assign credit for data．从历史上看，科学家反对分享有很多原因：这是很多工作；直到最近，还没有好的数据库；资助者没有推动共享；很难就格式化数据的标准达成一致意见；而且没有商定的方式为数据分配信用．可知，相信研究数据是私人知识产权可能阻碍开放数据共享．故选C．
34．C．细节理解题．根据第三段But the barriers are disappearing， in part because journals and funding agencies worldwide are encouraging scientists to make their data public．但障碍正在消失，部分原因是全球期刊和资助机构鼓励科学家公开他们的数据．可知，期刊和资助者态度的变化有助于解除开放数据共享的一些障碍．故选C．
35．B．细节理解题．根据最后一段 For example， one of the most popular data sets on multidisciplinary repository Dryad is about wood density around the world；例如，关于多学科资源库Dryad的最受欢迎的数据集之一是关于世界各地的木材密度；它已被下载了5700次．可知，Dryad就是一个例子，展示了开放数据共享如何使共享者和用户受益．故选B．
33．C．细节理解题．根据第二段 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 there is no agreed way to assign credit for data．从历史上看，科学家反对分享有很多原因：这是很多工作；直到最近，还没有好的数据库；资助者没有推动共享；很难就格式化数据的标准达成一致意见；而且没有商定的方式为数据分配信用．可知，相信研究数据是私人知识产权可能阻碍开放数据共享．故选C．
34．C．细节理解题．根据第三段But the barriers are disappearing， in part because journals and funding agencies worldwide are encouraging scientists to make their data public．但障碍正在消失，部分原因是全球期刊和资助机构鼓励科学家公开他们的数据．可知，期刊和资助者态度的变化有助于解除开放数据共享的一些障碍．故选C．
35．B．细节理解题．根据最后一段 For example， one of the most popular data sets on multidisciplinary repository Dryad is about wood density around the world；例如，关于多学科资源库Dryad的最受欢迎的数据集之一是关于世界各地的木材密度；它已被下载了5700次．可知，Dryad就是一个例子，展示了开放数据共享如何使共享者和用户受益．故选B．
解析
考查要点：本题主要考查学生对文章主旨和细节的理解能力，需结合上下文分析作者观点及具体事例的作用。
解题思路：
- 定位关键句：根据题干关键词（如“generally accept”“hinder”等）快速定位相关段落。
- 排除干扰项：注意区分文章明确表述与隐含观点，避免过度推断。
- 理解事例功能：如第35题需明确Dryad案例的作用是说明共享的双向受益性。
第32题
关键句：第一段首句“Although many researchers broadly agree that public access to raw data would accelerate science...”
解析：文章开篇指出，尽管研究人员不愿公开数据，但他们普遍认为开放数据有利于科学进步（选项D）。其他选项（如A的“保护专利”、C的“医学最重要”）均未在文中提及。
第33题
关键句：第二段“Historically, scientists have objected to sharing...it has been difficult to agree on standards for formatting data”
解析：科学家反对共享的原因包括数据视为“私人财产”（选项C），而非“担心盈利”（D）或“缺乏研究文化”（B）。文中未提及“大量复制”（A）的担忧。
第34题
关键句：第三段“But the barriers are disappearing, in part because journals and funding agencies worldwide are encouraging scientists to make their data public”
解析：障碍减少的关键原因是期刊和资助机构态度转变（选项C），而非“大数据需求”（A）或“技术进步”（B）。选项D“社会经济趋势”与原文无关。
第35题
关键句：最后一段“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”
解析：Dryad案例通过高下载量说明共享者获得关注（如Amy Zanne的引用），同时用户（如气候学家、林业工作者）也能受益，体现双向获益（选项B）。