Knowledge graphs are a key technique for linking and integrating cross-domain data, concepts, tools, and knowledge to enable data-driven analytics. As much of the worlds data have become massive in size, visualizing graph entities and their interrelationships intuitively and interactively has become a crucial task for ingesting and better utilizing graph content to support semantic reasoning, discovering hidden knowledge discovering, and better scientific understanding of geophysical and social phenomena. Despite the fact that many such phenomena (e.g., disasters) have clear spatial footprints and geographical properties, their location information is considered only as a textual label in existing graph visualization tools, limiting their capability to reveal the geospatial distribution patterns of the graph nodes. In addition, most graph visualization techniques rely on 2D graph visualization, which constraints the dimensions of information that can be presented and lacks support for graph structure examination from multiple angles. To tackle the above challenges, we developed a novel 3D map-based graph visualization algorithm to enable interactive exploration of graph content and patterns in a spatially explicit manner. The algorithm extends a 3D force directed graph by integrating a web map, an additional geolocational force, and a force balancing variable that allows for the dynamic adjustment of the 3D graph structure and layout. This mechanism helps create a balanced graph view between the semantic forces among the graph nodes and the attractive force from a geolocation to a graph node. Our solution offers a new perspective in visualizing and understanding spatial entities and events in a knowledge graph.

翻译：知识图谱是连接和整合跨领域数据、概念、工具及知识以支持数据驱动分析的关键技术。随着全球数据规模日趋庞大，直观且交互式地可视化图谱实体及其相互关系，已成为吸收并更好利用图谱内容以支持语义推理、发现隐藏知识、以及更科学地理解地球物理和社会现象的关键任务。尽管许多此类现象（如灾害）具有明确的空间足迹和地理属性，现有图谱可视化工具仅将其位置信息作为文本标签处理，限制了揭示图谱节点地理空间分布模式的能力。此外，多数图谱可视化技术依赖二维图谱可视化，这限制了可呈现的信息维度，且缺乏从多角度进行图谱结构检查的支持。为应对上述挑战，我们开发了一种新颖的基于三维地图的图谱可视化算法，支持以空间显式方式交互式探索图谱内容与模式。该算法通过集成网络地图、额外地理定位力及力平衡变量扩展了三维力导向图，允许动态调整三维图谱结构与布局。该机制有助于在图谱节点间的语义力与地理位置对节点的吸引力之间创建均衡的图谱视图。我们的解决方案为可视化和理解知识图谱中的空间实体与事件提供了全新视角。