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衡量研究数据的价值:海洋学数据集的引文分析

Measuring the value of research data: a citation analysis of oceanographic data sets.

作者信息

Belter Christopher W

机构信息

LAC Group, Central Library, National Oceanic and Atmospheric Administration, Silver Spring, Maryland, United States of America.

出版信息

PLoS One. 2014 Mar 26;9(3):e92590. doi: 10.1371/journal.pone.0092590. eCollection 2014.

Abstract

Evaluation of scientific research is becoming increasingly reliant on publication-based bibliometric indicators, which may result in the devaluation of other scientific activities--such as data curation--that do not necessarily result in the production of scientific publications. This issue may undermine the movement to openly share and cite data sets in scientific publications because researchers are unlikely to devote the effort necessary to curate their research data if they are unlikely to receive credit for doing so. This analysis attempts to demonstrate the bibliometric impact of properly curated and openly accessible data sets by attempting to generate citation counts for three data sets archived at the National Oceanographic Data Center. My findings suggest that all three data sets are highly cited, with estimated citation counts in most cases higher than 99% of all the journal articles published in Oceanography during the same years. I also find that methods of citing and referring to these data sets in scientific publications are highly inconsistent, despite the fact that a formal citation format is suggested for each data set. These findings have important implications for developing a data citation format, encouraging researchers to properly curate their research data, and evaluating the bibliometric impact of individuals and institutions.

摘要

科研评估越来越依赖基于出版物的文献计量指标,这可能导致其他科学活动(如数据管理)的价值被低估,而这些活动不一定会产生科学出版物。这个问题可能会破坏在科学出版物中公开共享和引用数据集的趋势,因为如果研究人员不太可能因整理研究数据而获得认可,他们就不太可能投入必要的精力来进行数据管理。本分析试图通过为存档于美国国家海洋学数据中心的三个数据集生成引用次数,来证明经过妥善整理且可公开获取的数据集的文献计量影响。我的研究结果表明,所有这三个数据集都被大量引用,在大多数情况下,估计的引用次数高于同一年在《海洋学》上发表的所有期刊文章的99%。我还发现,尽管每个数据集都建议采用正式的引用格式,但在科学出版物中引用和提及这些数据集的方法却高度不一致。这些发现对于制定数据引用格式、鼓励研究人员妥善整理他们的研究数据以及评估个人和机构的文献计量影响具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d2b/3966791/d0a4f4331945/pone.0092590.g001.jpg

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