Improving Wikidata with Student-Generated Concept Maps
Improving Wikidata with Student-Generated Concept Maps
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DOI：
10.1609/icwsm.v16i1.19285
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发表时间：
2022-05
期刊：
影响因子：
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通讯作者：
Hayden Freedman;A. Hoek;Bill Tomlinson
中科院分区：
文献类型：
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作者：
Hayden Freedman;A. Hoek;Bill Tomlinson
维基数据是一个公开的、众包的知识库，包含了为智能系统所使用而构建的相互关联的概念。虽然维基数据经历了快速的增长，但它还远远没有完成，并且面临着阻碍其充分发挥潜力的挑战。在本文中，我们提出了一种新的方法，通过让本科生通过概念映射作业来贡献以前缺失的知识来改进维基数据。而不是让学生直接编辑维基数据，我们描述了一个工作流程，其中知识是由学生构建，然后由专家审查。我们提出了一个案例研究，在其中我们部署了一个工作流在一个大型的本科课程的可持续发展，并发现它能够贡献大量的高质量的声明，坚持和贡献以前缺少的知识维基数据。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。
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.