Why data citation isn't working, and what to do about it
Why data citation isn't working, and what to do about it
复制标题
为什么数据引用不起作用以及该怎么办
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Yinjun Wu
中科院分区：
文献类型：
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作者：
P. Buneman;Greig Christie;J. Davies;Roza Dimitrellou;S. Harding;Adam J Pawson;J. Sharman;Yinjun Wu
摘要我们描述了一个系统，它从一个精选的数据库中自动生成一个简短的传统出版物的集合--引文摘要--这些出版物描述了数据库的各个组成部分的内容。这些摘要的目的是确保数据库的贡献者通过目前使用的h指数等措施获得适当的积分。此外，这些摘要也为数据库引用的出版物和人物提供了信任。在执行此操作时，我们需要处理粒度--应该生成多少摘要才能有效地表示对数据库的贡献？我们还需要处理演变-当数据库在演变时，给定的摘要可以在多长时间内充当适当的参考？我们描述了一本专门为包含这些引文摘要而定制的期刊。我们还简要讨论了当前记录引用的机制对数据引用的过程和价值施加的限制。
Abstract We describe a system that automatically generates from a curated database a collection of short conventional publications—citation summaries—that describe the contents of various components of the database. The purpose of these summaries is to ensure that the contributors to the database receive appropriate credit through the currently used measures such as h-indexes. Moreover, these summaries also serve to give credit to publications and people that are cited by the database. In doing this, we need to deal with granularity—how many summaries should be generated to represent effectively the contributions to a database? We also need to deal with evolution—for how long can a given summary serve as an appropriate reference when the database is evolving? We describe a journal specifically tailored to contain these citation summaries. We also briefly discuss the limitations that the current mechanisms for recording citations place on both the process and value of data citation.