Improving Wikidata with Student-Generated Concept Maps

Hayden Freedman, A. Hoek, Bill Tomlinson
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Abstract

Wikidata is a publicly available, crowdsourced knowledge base that contains interlinked concepts structured for use by intelligent systems. While Wikidata has experienced rapid growth, it is far from complete and faces challenges that prevent it from being used to its full potential. In this paper, we propose a novel method for improving Wikidata by engaging undergraduate students to contribute previously missing knowledge via concept mapping assignments. Rather than allow students to edit Wikidata directly, we describe a workflow in which knowledge is constructed by students and then reviewed by an expert. We present a case study in which we deployed a workflow in a large undergraduate course about sustainability, and find that it was able to contribute a substantial number of high quality statements that persisted in and contributed previously missing knowledge to Wikidata. This work provides a preliminary workflow for improving Wikidata based on classroom assignments, as well as recommendations for how future educational projects could continue to improve Wikidata or other public knowledge bases.
用学生生成的概念图改进维基数据
维基数据是一个公开可用的、众包的知识库,它包含了供智能系统使用的相互关联的概念。虽然维基数据经历了快速增长,但它还远未完成,并面临着阻碍其充分发挥潜力的挑战。在本文中,我们提出了一种改进维基数据的新方法,即通过概念映射作业让本科生贡献以前缺失的知识。我们不允许学生直接编辑维基数据,而是描述了一个工作流,其中知识由学生构建,然后由专家审查。我们提出了一个案例研究,我们在一个关于可持续性的大型本科课程中部署了一个工作流,并发现它能够提供大量高质量的陈述,这些陈述持续存在,并为维基数据提供了以前缺失的知识。这项工作提供了一个基于课堂作业改进维基数据的初步工作流程,以及未来教育项目如何继续改进维基数据或其他公共知识库的建议。
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