<b>A dataset on the spatiotemporal distributions of street and neighborhood crime in China</b>
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Crime is a significant social, economic, and legal issue. This paper presents an open-access spatiotemporal repository of street and neighborhood crime data, comprising approximately one million records of crimes in China, with specific geographic coordinates (latitude and longitude) and timestamps for each incident. The dataset is based on publicly available law court judgment documents. Artificial intelligence (AI) technologies are employed to extract crime events at the neighborhood or even building level from vast amounts of unstructured judicial text. This dataset enables more precise spatial analysis of crime incidents, offering valuable insights across interdisciplinary fields such as economics, sociology, and geography. It contributes significantly to the achievement of the United Nations Sustainable Development Goals (SDGs), particularly in fostering sustainable cities and communities, and plays a crucial role in advancing efforts to reduce all forms of violence and related mortality rates.citation: Zhang Y, Kwan M P, Fang L. An LLM driven dataset on the spatiotemporal distributions of street and neighborhood crime in China[J]. Scientific Data, 2025, 12(1): 467.<b>Download version 3!!! Previous bugs have been fixed.</b><b>请下载version3！！！之前的版本bug已经修复。</b>关于该数据的问题可以访问我的个人网站获取我的联系方式：https://www.giserzhang.xyz/
犯罪是一类重要的社会、经济与法律议题。本文构建了一个面向街道与社区犯罪数据的开放获取的时空数据集仓库，包含中国境内约100万条犯罪记录，每条记录均附带精确的地理坐标（纬度与经度）以及事件发生时间戳。该数据集基于公开可获取的法院裁判文书构建。本研究借助人工智能（Artificial Intelligence, AI）技术，从海量非结构化司法文本中提取出社区乃至楼宇级别的犯罪事件信息。本数据集支持对犯罪事件开展更为精准的空间分析，可为经济学、社会学、地理学等跨学科领域提供极具价值的研究视角。该数据集对联合国可持续发展目标（Sustainable Development Goals, SDGs）的达成具有重要贡献，尤其在推动可持续城市与社区建设方面，并为降低各类暴力行为及相关死亡率的工作提供关键支撑。引用格式：Zhang Y, Kwan M P, Fang L. 中国街道与社区犯罪时空分布的大语言模型（Large Language Model, LLM）驱动数据集[J]. Scientific Data, 2025, 12(1): 467.<b>请下载版本3！！！此前版本存在的程序漏洞已完成修复。</b>关于该数据的问题可以访问我的个人网站获取我的联系方式：https://www.giserzhang.xyz/
