Wikimpacts 1.0: a new global climate impact database based on automated information extraction from Wikipedia

作者：Ni Li, Wim Thiery, Shorouq Zahra, Mariana Madruga de Brito, Koffi Worou, Murathan Kurfali, Seppe Lampe, Paúl Muñoz, Clare M. Flynn, Camila Trigoso, Joakim Nivre, Jakob Zscheischler, Gabriele Messori · 发表于：Natural hazards and earth system sciences · 年份：2026 · DOI：10.5194/nhess-26-2609-2026 · 被引用次数：2 · 研究领域：Wikis in Education and Collaboration、Web Data Mining and Analysis

Abstract. Climate extremes like storms, heatwaves, wildfires, droughts and floods significantly threaten society and ecosystems. However, comprehensive data on the socio-economic impacts of climate extremes remains limited. Here we present Wikimpacts 1.0, a global climate impact database built by extracting information from Wikipedia using natural language processing. Our method identifies relevant articles, extracts the information using GPT4o, post-processes the information and consolidates the database. Impact data is stored at the event, national, and sub-national levels, covering 2726 events from 1034 to 2024, with 17 912 national and 32 343 sub-national entries. The database shows low error scores (range from 0 to 1) for event-level information like timing (0.05), deaths (0.03), and economic damage (0.12), and slightly higher error scores for injuries (0.21), homelessness (0.25), displacement (0.29), and damaged buildings (0.28) compared to manually annotated data from 156 events. Wikimpacts 1.0 provides a different event coverage than EM-DAT, notably providing broader coverage of storm impacts but more limited coverage of flood impacts. We match 179 events between the two databases to compare impact values, and find that 32 out of 179 matched events have identical data for deaths, and 7 out of 77 for injuries. However, there are notable discrepancies in information on homelessness and damage. We view the publicly available Wikimpacts 1.0 database as a complementary res...