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实时文献计量学：Dimensions作为分析COVID-19相关方面的资源

Real-Time Bibliometrics: Dimensions as a Resource for Analyzing Aspects of COVID-19.

作者信息

Hook Daniel W, Porter Simon J, Draux Hélène, Herzog Christian T

机构信息

Centre for Complexity Science, Imperial College London, London, United Kingdom.

Department of Physics, Washington University in St Louis, St Louis, MO, United States.

出版信息

Front Res Metr Anal. 2021 Jan 12;5:595299. doi: 10.3389/frma.2020.595299. eCollection 2020.

DOI:10.3389/frma.2020.595299
PMID:33969256
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8104272/
Abstract

Dimensions was built as a platform to allow stakeholders in the research community, including academic bibliometricians, to more easily create and understand the context of different types of research object through the linkages between these objects. Links between objects are created via persistent identifiers and machine learning techniques, while additional context is introduced via data enhancements such as per-object categorisations and person and institution disambiguation. While these features make analytical use cases accessible for end users, the COVID-19 crisis has highlighted a different set of needs to analyze trends in scholarship as they occur: Real-time bibliometrics. The combination of full-text search, daily data updates, a broad set of scholarly objects including pre-prints and a wider set of data fields for analysis, broadens opportunities for a different style of analysis. A subset of these emerging capabilities is discussed and three basic analyses are presented as illustrations of the potential for real-time bibliometrics.

摘要

Dimensions被构建为一个平台，使研究界的利益相关者，包括学术文献计量学家，能够通过这些对象之间的联系，更轻松地创建和理解不同类型研究对象的背景。对象之间的链接通过持久标识符和机器学习技术创建，而额外的背景则通过数据增强来引入，例如按对象分类以及人物和机构的去重。虽然这些功能使终端用户能够使用分析用例，但新冠疫情危机凸显了另一组需求，即分析学术研究中实时出现的趋势：实时文献计量学。全文搜索、每日数据更新、包括预印本在内的广泛学术对象以及更广泛的分析数据字段的结合，为不同风格的分析提供了更多机会。本文讨论了这些新兴功能的一个子集，并给出了三项基本分析，以说明实时文献计量学的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a85/8104272/91e7e3dee6f1/frma-05-595299-g012.jpg
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