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在你能找到最多内容的地方进行搜索:比较56个书目数据库的学科覆盖范围。

Search where you will find most: Comparing the disciplinary coverage of 56 bibliographic databases.

作者信息

Gusenbauer Michael

机构信息

University of Innsbruck, Innsbruck, Austria.

出版信息

Scientometrics. 2022;127(5):2683-2745. doi: 10.1007/s11192-022-04289-7. Epub 2022 May 6.

Abstract

This paper introduces a novel scientometrics method and applies it to estimate the subject coverages of many of the popular English-focused bibliographic databases in academia. The method uses query results as a common denominator to compare a wide variety of search engines, repositories, digital libraries, and other bibliographic databases. The method extends existing sampling-based approaches that analyze smaller sets of database coverages. The findings show the relative and absolute subject coverages of 56 databases-information that has often not been available before. Knowing the databases' subject coverage allows the selection of the most comprehensive databases for searches requiring high recall/sensitivity, particularly relevant in lookup or exploratory searches. Knowing the databases' subject coverage allows the selection of specialized databases for searches requiring high precision/specificity, particularly relevant in systematic searches. The findings illustrate not only differences in the disciplinary coverage of Google Scholar, Scopus, or Web of Science, but also of less frequently analyzed databases. For example, researchers might be surprised how Meta (discontinued), Embase, or Europe PMC are found to cover more records than PubMed in Medicine and other health subjects. These findings should encourage researchers to re-evaluate their go-to databases, also against newly introduced options. Searching with more comprehensive databases can improve finding, particularly when selecting the most fitting databases needs particular thought, such as in systematic reviews and meta-analyses. This comparison can also help librarians and other information experts re-evaluate expensive database procurement strategies. Researchers without institutional access learn which open databases are likely most comprehensive in their disciplines.

摘要

本文介绍了一种新颖的科学计量学方法,并将其应用于估计学术界许多流行的以英语为重点的文献数据库的学科覆盖范围。该方法使用查询结果作为公分母,以比较各种各样的搜索引擎、存储库、数字图书馆和其他文献数据库。该方法扩展了现有的基于抽样的方法,这些方法分析的是较小的数据库覆盖范围集。研究结果显示了56个数据库的相对和绝对学科覆盖范围——这些信息以前往往无法获得。了解数据库的学科覆盖范围有助于为需要高召回率/敏感度的搜索选择最全面的数据库,这在查找或探索性搜索中尤为重要。了解数据库的学科覆盖范围有助于为需要高精度/特异性的搜索选择专门的数据库,这在系统搜索中尤为重要。研究结果不仅说明了谷歌学术、Scopus或科学网在学科覆盖方面的差异,也说明了较少被分析的数据库的差异。例如,研究人员可能会惊讶地发现,Meta(已停用)、Embase或欧洲生物医学文献数据库在医学和其他健康学科方面所涵盖的记录比PubMed更多。这些发现应鼓励研究人员重新评估他们常用的数据库,同时也考虑新推出的选项。使用更全面的数据库进行搜索可以提高检索效率,特别是在选择最合适的数据库需要特别考虑时,例如在系统评价和荟萃分析中。这种比较还可以帮助图书馆员和其他信息专家重新评估昂贵的数据库采购策略。没有机构访问权限的研究人员可以了解哪些开放数据库在其学科领域可能最全面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fcb7/9075928/adfe99067579/11192_2022_4289_Fig1_HTML.jpg

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