Peter Buneman, Dennis Dosso, Matteo Lissandrini, Gianmaria Silvello, He Sun
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引用次数: 0
摘要
在传播科学和统计数据方面,在线数据库几乎完全取代了期刊和参考文献等传统纸质媒体。既然如此,我们能否像衡量作者或期刊的影响力那样来衡量数据库的影响力呢?要做到这一点,我们需要以某种方式将数据库表示为一组出版物,而数据库通常允许大量可能的分解,其中任何一部分都可以被视为出版物。我们证明了 h 指数的定义可以自然地扩展到层次结构,因此,如果数据库允许某种层次结构的解释,我们就可以用它来衡量数据库的重要性;此外,它的计算效率与计算普通的 h 指数一样高。这也为我们提供了数据库的分解方法,可用于其他目的,例如为数据库的策划者或贡献者提供荣誉。我们通过分析三个广泛使用的数据库来说明这一过程。
In disseminating scientific and statistical data, on-line databases have
almost completely replaced traditional paper-based media such as journals and
reference works. Given this, can we measure the impact of a database in the
same way that we measure an author's or journal's impact? To do this, we need
somehow to represent a database as a set of publications, and databases
typically allow a large number of possible decompositions into parts, any of
which could be treated as a publication. We show that the definition of the h-index naturally extends to hierarchies,
so that if a database admits some kind of hierarchical interpretation we can
use this as one measure of the importance of a database; moreover, this can be
computed as efficiently as one can compute the normal h-index. This also gives
us a decomposition of the database that might be used for other purposes such
as giving credit to the curators or contributors to the database. We illustrate
the process by analyzing three widely used databases.