Community-level event (CLE) datasets, such as police reports of crime events, contain abundant semantic information of event situations, and descriptions in a geospatial-temporal context. They are critical for frontline users, such as police officers and social workers, to discover and examine insights about community neighborhoods. We propose CLEVis, a neighborhood visual analytics system for CLE datasets, to help frontline users explore events for insights at community regions of interest, namely fine-grained geographical resolutions, such as small neighborhoods around local restaurants, churches, and schools. CLEVis fully utilizes semantic information by integrating automatic algorithms and interactive visualizations. The design and development of CLEVis are conducted with solid collaborations with real-world community workers and social scientists. Case studies and user feedback are presented with real-world datasets and applications.

中文翻译：

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CLEVis：用于社区级别活动的语义驱动视觉分析系统


社区级事件（CLE）数据集，例如警方对犯罪事件的报告，包含丰富的事件情况语义信息以及地理时空上下文中的描述。它们对于警察和社会工作者等一线用户发现和检查有关社区的见解至关重要。我们提出了 CLEVis，这是一种针对 CLE 数据集的邻里可视化分析系统，帮助一线用户探索感兴趣的社区区域的事件，即细粒度的地理分辨率，例如当地餐馆、教堂和学校周围的小社区。 CLEVis 通过集成自动算法和交互式可视化来充分利用语义信息。 CLEVis 的设计和开发是通过与现实世界的社区工作者和社会科学家的密切合作进行的。案例研究和用户反馈通过真实世界的数据集和应用程序提供。