This dataset constructed from 532 reports improves regulatory authorities' ability for risk prevention in mining safety.
Mine accidents pose severe threats to worker safety and sustainable mining development in China. However, existing mine accident data in China are often scattered, unstructured, and lack systematic integration, which limits their application in safety research and practice. This study constructed a standardized structured dataset using 532 mine accident reports from official channels covering the period 2010–2025. The dataset went through four stages: data collection, standardized cleaning, structured annotation, and quality validation. It is stored in JSON Lines (JSONL) format for easy reuse. The dataset covers 27 provinces/autonomous regions/municipalities in China. Among accident levels, general accidents account for 65.6%; among accident types, roof accidents account for 20.3%. Accidents are geographically concentrated, with 11.7%, 8.3%, and 7.7% occurring in Shanxi, Gansu, and Inner Mongolia, respectively. Official data have shown an annual average decrease of 9.7% in mine accidents from 2018 to 2022, reflecting improved safety governance. This dataset addresses the gap of a full-element structured mine accident database in China, providing high-quality data for accident causation modeling, regional risk early warning, and safety policy evaluation. It also supports mine enterprises in targeted risk prevention and regulatory authorities in precise regulatory enforcement.
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Li et al. (2025) studied this question.
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