Stanford Center for Biomedical Informatics Research, Stanford University, Medical School Office Building X215, Stanford, CA 94305, USA.
Sci Data. 2018 Mar 20;5:180043. doi: 10.1038/sdata.2018.43.
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.
衡量信息学资源（如软件工具和数据库）的使用情况对于量化其影响、价值和投资回报至关重要。我们开发了一个公开可用的信息学资源出版物及其引文网络数据集，以及一个相关的指标（u-Index），以衡量信息学资源随时间推移的影响。我们的数据集区分了引文出现的上下文，以区分“意识”和“使用”，并使用开放获取出版物的引用宇宙来计算引文数量以量化影响。使用次数引文与意识引文之比高的资源很可能被其他人广泛使用，并且具有较高的 u-Index 得分。我们已经预先计算了近 100,000 个信息学资源的 u-Index。我们展示了如何使用 u-Index 来跟踪信息学资源随时间推移的影响。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 而编译的数据集都是公开可用的。
