An analysis of discussions in collaborative knowledge engineering through the lens of Wikidata

IF 2.1 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Web Semantics Pub Date : 2023-10-01 DOI:10.1016/j.websem.2023.100799
Elisavet Koutsiana, Gabriel Maia Rocha Amaral, Neal Reeves, Albert Meroño-Peñuela, Elena Simperl
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Abstract

We study discussions in Wikidata, the world’s largest open-source collaborative knowledge graph (KG). This is important because it helps KG community managers understand how discussions are used and inform the design of collaborative practices and support tools. We follow a mixed-methods approach with descriptive statistics, thematic analysis, and statistical tests to investigate how much discussions in Wikidata are used, what they are used for, and how they support knowledge engineering (KE) activities. The study covers three core sources of discussion, the talk pages that accompany Wikidata items and properties, and a general-purpose communication page. Our findings show low use of discussion capabilities and a power-law distribution similar to other KE projects such as Schema.org. When discussions are used, they are mostly about KE activities, including activities that span across the entire KE lifecycle from conceptualisation and implementation to maintenance and taxonomy building. We hope that the findings will help Wikidata devise improved practices and capabilities to encourage the use of discussions as a tool to collaborate, improve editor engagement, and engineer better KGs.

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从维基数据的角度分析协同知识工程中的讨论
我们在世界上最大的开源协作知识图谱(KG)Wikidata中研究讨论。这一点很重要,因为它有助于KG社区管理人员了解如何使用讨论,并为协作实践和支持工具的设计提供信息。我们采用描述性统计、主题分析和统计测试的混合方法来调查维基数据中的讨论被使用了多少,它们被用于什么,以及它们如何支持知识工程(KE)活动。这项研究涵盖了三个核心讨论来源,即维基数据项目和属性附带的谈话页面,以及一个通用通信页面。我们的研究结果表明,与Schema.org等其他KE项目类似,讨论能力的使用率很低,幂律分布也很低。当使用讨论时,它们主要是关于KE活动的,包括从概念化和实现到维护和分类构建的整个KE生命周期的活动。我们希望这些发现将有助于维基数据设计改进的实践和能力,鼓励将讨论作为合作的工具,提高编辑参与度,并设计更好的KG。
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来源期刊
Journal of Web Semantics
Journal of Web Semantics 工程技术-计算机:人工智能
CiteScore
6.20
自引率
12.00%
发文量
22
审稿时长
14.6 weeks
期刊介绍: The Journal of Web Semantics is an interdisciplinary journal based on research and applications of various subject areas that contribute to the development of a knowledge-intensive and intelligent service Web. These areas include: knowledge technologies, ontology, agents, databases and the semantic grid, obviously disciplines like information retrieval, language technology, human-computer interaction and knowledge discovery are of major relevance as well. All aspects of the Semantic Web development are covered. The publication of large-scale experiments and their analysis is also encouraged to clearly illustrate scenarios and methods that introduce semantics into existing Web interfaces, contents and services. The journal emphasizes the publication of papers that combine theories, methods and experiments from different subject areas in order to deliver innovative semantic methods and applications.
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