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量化科学数据库的一致性。

Quantifying the consistency of scientific databases.

作者信息

Šubelj Lovro, Bajec Marko, Boshkoska Biljana Mileva, Kastrin Andrej, Levnajić Zoran

机构信息

Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia.

Faculty of Information Studies in Novo mesto, Novo mesto, Slovenia.

出版信息

PLoS One. 2015 May 18;10(5):e0127390. doi: 10.1371/journal.pone.0127390. eCollection 2015.

Abstract

Science is a social process with far-reaching impact on our modern society. In recent years, for the first time we are able to scientifically study the science itself. This is enabled by massive amounts of data on scientific publications that is increasingly becoming available. The data is contained in several databases such as Web of Science or PubMed, maintained by various public and private entities. Unfortunately, these databases are not always consistent, which considerably hinders this study. Relying on the powerful framework of complex networks, we conduct a systematic analysis of the consistency among six major scientific databases. We found that identifying a single "best" database is far from easy. Nevertheless, our results indicate appreciable differences in mutual consistency of different databases, which we interpret as recipes for future bibliometric studies.

摘要

科学是一个对现代社会有着深远影响的社会过程。近年来,我们首次能够对科学本身进行科学研究。这得益于越来越多可获取的关于科学出版物的海量数据。这些数据包含在诸如科学引文索引(Web of Science)或医学期刊数据库(PubMed)等多个数据库中,由各种公共和私人实体维护。不幸的是,这些数据库并不总是一致的,这在很大程度上阻碍了这项研究。依靠复杂网络的强大框架,我们对六个主要科学数据库之间的一致性进行了系统分析。我们发现确定一个单一的“最佳”数据库绝非易事。然而,我们的结果表明不同数据库之间在相互一致性方面存在明显差异,我们将其解释为未来文献计量学研究的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9bbf/4436008/0a06ef476ef3/pone.0127390.g001.jpg

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