Who shares? Who doesn't? Factors associated with openly archiving raw research data.
Who shares? Who doesn't? Factors associated with openly archiving raw research data.
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DOI：
10.1371/journal.pone.0018657
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发表时间：
2011
期刊：
影响因子：
3.7
通讯作者：
Piwowar HA
中科院分区：
文献类型：
--
作者：
Piwowar HA
许多倡议鼓励研究人员分享他们的原始数据集，希望提高研究效率和质量。尽管有这些时间和金钱的投入，但我们并不清楚谁公开分享原始研究数据，谁不分享，以及哪些举措与高数据共享率相关。在这项分析中，我使用文献计量学的方法来确定研究人员在研究发表后公开存档他们的原始基因表达微阵列数据集的频率模式。自动化方法确定了2000至2009年间发表的描述基因表达微阵列数据创建的11,603篇文章。在这些文章中，25%的文章在最佳实践存储库中找到了相关的数据集，从2001年的不到5%增加到2007-2009年的30%-35%。考虑到自动化方法的敏感性，最近的基因表达研究中，大约45%的数据是公开的。对124篇不同文献计量学属性的一阶因子分析揭示了描述作者、资金、机构、出版和领域环境的15个因子。在多元回归中，如果作者有分享或重复使用数据的经验，如果他们的研究发表在开放获取期刊或数据共享政策相对较强的期刊上，或者如果研究得到了大量NIH拨款的资助，那么作者最有可能分享数据。癌症和人类研究的作者最不可能提供他们的数据集。这些结果表明，研究数据共享水平仍然很低，而且增长缓慢，在可能产生最大影响的领域，数据最少可用。让我们向那些高共享率的人学习，以充分发挥我们的研究成果的潜力。
Many initiatives encourage investigators to share their raw datasets in hopes of increasing research efficiency and quality. Despite these investments of time and money, we do not have a firm grasp of who openly shares raw research data, who doesn't, and which initiatives are correlated with high rates of data sharing. In this analysis I use bibliometric methods to identify patterns in the frequency with which investigators openly archive their raw gene expression microarray datasets after study publication. Automated methods identified 11,603 articles published between 2000 and 2009 that describe the creation of gene expression microarray data. Associated datasets in best-practice repositories were found for 25% of these articles, increasing from less than 5% in 2001 to 30%–35% in 2007–2009. Accounting for sensitivity of the automated methods, approximately 45% of recent gene expression studies made their data publicly available. First-order factor analysis on 124 diverse bibliometric attributes of the data creation articles revealed 15 factors describing authorship, funding, institution, publication, and domain environments. In multivariate regression, authors were most likely to share data if they had prior experience sharing or reusing data, if their study was published in an open access journal or a journal with a relatively strong data sharing policy, or if the study was funded by a large number of NIH grants. Authors of studies on cancer and human subjects were least likely to make their datasets available. These results suggest research data sharing levels are still low and increasing only slowly, and data is least available in areas where it could make the biggest impact. Let's learn from those with high rates of sharing to embrace the full potential of our research output.
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影响因子：
2.7
作者：
Bitzer, Juergen;Schrettl, Wolfram;Schroeder, Philipp J. H.
通讯作者：
Schroeder, Philipp J. H.
DOI：
10.1002/asi.10289
发表时间：
2003-08-01
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作者：
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作者：
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通讯作者：
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作者：
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通讯作者：
Louis, KS
DOI：
10.1002/asi.21016
发表时间：
2009-06-01
影响因子：
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作者：
Bornmann, Lutz;Mutz, Ruediger;Daniel, Hans-Dieter
通讯作者：
Daniel, Hans-Dieter