Wikidata is a multi-language knowledge base that is being edited and maintained by editors from different language communities. Due to the structured nature of its content, the contributions are in various forms, including manual edit, tool-assisted edits, automated edits, etc, with the majority of edits being the import from wiki-internal or external datasets. Due to the outstanding power of bots and tools reflecting from their large volume of edits, knowledge contributions within Wikidata can easily cause epistemic injustice due to internal and external reasons. In this case study, we compared the coverage and edit history of human pages in two countries. By shedding light on these disparities and offering actionable solutions, our study aims to enhance the fairness and inclusivity of knowledge representation within Wikidata, ultimately contributing to a more equitable and comprehensive global knowledge base.

翻译：维基数据是一个多语言知识库，由来自不同语言社区的编辑者共同编辑和维护。由于其内容的结构化特性，贡献形式多样，包括手动编辑、工具辅助编辑、自动化编辑等，其中大部分编辑来自维基内部或外部数据集的导入。由于机器人和工具反映出的海量编辑量所带来的显著影响力，维基数据中的知识贡献很容易因内部和外部原因导致认知不公。在本案例研究中，我们比较了两个国家人物页面的覆盖率和编辑历史。通过揭示这些差异并提供可行的解决方案，本研究旨在提升维基数据知识表征的公平性与包容性，最终为构建一个更公平、更全面的全球知识库做出贡献。