科学知识图谱和研究影响评估的新趋势

IF 4.1 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE

Quantitative Science Studies Pub Date : 2021-11-05 DOI:10.1162/qss_e_00160

P. Manghi, A. Mannocci, Francesco Osborne, Dimitris Sacharidis, Angelo Salatino, Thanasis Vergoulis

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引用次数: 10

摘要

近几十年来，我们经历了科学文章和相关研究对象(如数据集、软件包)的发表率不断增加。随着这一趋势的不断发展，学术知识领域的从业者面临着一些挑战。在本期特刊中，我们重点关注这类挑战的两大类:(a)与学术数据组织相关的挑战，以实现灵活、上下文敏感、细粒度和机器可操作的学术知识表示，同时是结构化的、相互关联的和语义丰富的;(b)与设计新颖、可靠和全面的指标来评估科学影响相关的挑战。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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New trends in scientific knowledge graphs and research impact assessment

In recent decades, we have experienced a continuously increasing publication rate of scientific articles and related research objects (e.g., data sets, software packages). As this trend keeps growing, practitioners in the field of scholarly knowledge are confronted with several challenges. In this special issue, we focus on two major categories of such challenges: (a) those related to the organization of scholarly data to achieve a flexible, context-sensitive, finegrained, and machine-actionable representation of scholarly knowledge that at the same time is structured, interlinked, and semantically rich, and (b) those related to the design of novel, reliable, and comprehensive metrics to assess scientific impact.

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