A Novel Method for Resolving and Completing Authors’ Country Affiliation Data in Bibliographic Records

B. Nguyen, J. Dinneen, Markus Luczak-Rösch
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引用次数: 5

Abstract

Abstract Purpose Our work seeks to overcome data quality issues related to incomplete author affiliation data in bibliographic records in order to support accurate and reliable measurement of international research collaboration (IRC). Design/methodology/approch We propose, implement, and evaluate a method that leverages the Web-based knowledge graph Wikidata to resolve publication affiliation data to particular countries. The method is tested with general and domain-specific data sets. Findings Our evaluation covers the magnitude of improvement, accuracy, and consistency. Results suggest the method is beneficial, reliable, and consistent, and thus a viable and improved approach to measuring IRC. Research limitations Though our evaluation suggests the method works with both general and domain-specific bibliographic data sets, it may perform differently with data sets not tested here. Further limitations stem from the use of the R programming language and R libraries for country identification as well as imbalanced data coverage and quality in Wikidata that may also change over time. Practical implications The new method helps to increase the accuracy in IRC studies and provides a basis for further development into a general tool that enriches bibliographic data using the Wikidata knowledge graph. Originality This is the first attempt to enrich bibliographic data using a peer-produced, Web-based knowledge graph like Wikidata.
一种解决和完成书目记录中作者国别关系数据的新方法
摘要目的我们的工作旨在克服与书目记录中不完整的作者归属数据有关的数据质量问题,以支持准确可靠地衡量国际研究合作(IRC)。设计/方法论/方法我们提出、实施和评估了一种方法,该方法利用基于Web的知识图Wikidata来解决特定国家的出版物隶属关系数据。该方法使用通用和特定领域的数据集进行了测试。调查结果我们的评估涵盖了改进程度、准确性和一致性。结果表明,该方法是有益的、可靠的、一致的,因此是一种可行的、改进的IRC测量方法。研究局限性尽管我们的评估表明,该方法适用于一般和特定领域的书目数据集,但它可能对此处未测试的数据集表现不同。进一步的限制源于使用R编程语言和R库来识别国家,以及维基数据中不平衡的数据覆盖率和质量,这些也可能随着时间的推移而变化。实际意义新方法有助于提高IRC研究的准确性,并为进一步发展成为使用Wikidata知识图丰富书目数据的通用工具提供了基础。独创性这是第一次尝试使用类似Wikidata的同行制作的基于网络的知识图来丰富书目数据。
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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