U-Index, a dataset and an impact metric for informatics tools and databases.

U-Index, a dataset and an impact metric for informatics tools and databases.
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DOI:
10.1038/sdata.2018.43
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发表时间:
2018-03-20
期刊:
影响因子:
9.8
通讯作者:
Shah NH
Shah NH
中科院分区:
综合性期刊2区
文献类型:
--
作者:
Callahan A;Winnenburg R;Shah NH

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衡量软件工具和数据库等信息资源的使用情况对于量化其影响、价值和投资回报至关重要。我们已经开发了一个公开可用的信息资源出版物及其引文网络的数据集,以及一个相关的度量标准(u-Index)来衡量信息资源随时间的影响。我们的数据集区分了引文发生的上下文,以区分“意识”和“使用”,并使用开放获取出版物的引文宇宙来推导引文计数,以量化影响。使用引文与意识引文比例较高的资源可能会被其他人广泛使用,并具有较高的u-Index得分。我们已经为近100,000个信息学资源预先计算了u指数。我们演示了如何使用u-Index来跟踪随时间推移的信息学资源影响。计算u-Index指标的方法、预先计算的u-Index值以及我们为计算u-Index而汇编的数据集都是公开的。
Measuring the usage of informatics resources such as software tools and databases is essential to quantifying their impact, value and return on investment. We have developed a publicly available dataset of informatics resource publications and their citation network, along with an associated metric (u-Index) to measure informatics resources’ impact over time. Our dataset differentiates the context in which citations occur to distinguish between ‘awareness’ and ‘usage’, and uses a citing universe of open access publications to derive citation counts for quantifying impact. Resources with a high ratio of usage citations to awareness citations are likely to be widely used by others and have a high u-Index score. We have pre-calculated the u-Index for nearly 100,000 informatics resources. We demonstrate how the u-Index can be used to track informatics resource impact over time. The method of calculating the u-Index metric, the pre-computed u-Index values, and the dataset we compiled to calculate the u-Index are publicly available.
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