Map images with various themes and cartographic representations have become ubiquitous on the Internet. Such ubiquitously and openly accessible data, named ubiquitous map images in this study, are a potential resource for many geographic information applications such as cartographic design. However, there is a semantic gap between the simple physical form and the complex connotation of ubiquitous map images, which hinders their further applications. To mitigate such barrier, this article develops an ontology‐based semantic description model for ubiquitous map images. First, we discuss the design concerns and principles of the semantic description model of ubiquitous map images. Second, three semantic layers of the semantic description model are proposed, that is, image semantic description layer, cognitive tool layer, and information source layer, and detailed semantic description items are defined for each layer. Furthermore, a formalized semantic description model for ubiquitous map images is developed using ontology construction tools, which lays the foundation for automated and fine‐grained reasoning with the information embedded in map images. We construct a small test dataset consisting of weather maps, and use three types of constraints, namely “time‐topic,” “region‐topic,” and “map auxiliary elements” for the semantic retrieval experiments. The experiments show that the proposed semantic ontology model can enable complex semantic retrieval of ubiquitous map images. Finally, the scalability of the model is discussed from three perspectives: the depth of description, the combination with intelligent methods, and the integration with other open knowledge bases. The proposed model provides a semantic label system for applying data‐driven approaches to decode ubiquitous map images, which also paves the path to the development of cartographic theory in the era of information and communications technologies.

中文翻译：

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基于本体的泛在地图图像语义描述模型

具有各种主题和制图表示形式的地图图像在互联网上已经无处不在。这种无处不在且可公开访问的数据，在本研究中被称为“无处不在的地图图像”，是许多地理信息应用（例如制图设计）的潜在资源。然而，普遍存在的地图图像的简单物理形式和复杂内涵之间存在语义鸿沟，这阻碍了其进一步应用。为了减轻这种障碍，本文为无处不在的地图图像开发了一种基于本体的语义描述模型。首先讨论泛在地图图像语义描述模型的设计关注点和原则。其次，提出了语义描述模型的三个语义层，即图像语义描述层、认知工具层和信息源层，并为每一层定义了详细的语义描述项。此外，利用本体构建工具开发了针对普遍存在的地图图像的形式化语义描述模型，为利用地图图像中嵌入的信息进行自动化和细粒度推理奠定了基础。我们构建了一个由天气地图组成的小型测试数据集，并使用三种类型的约束，即“时间主题”、“区域主题”和“地图辅助元素”进行语义检索实验。实验表明，所提出的语义本体模型可以实现对无处不在的地图图像的复杂语义检索。最后从描述深度、与智能方法的结合、与其他开放知识库的集成三个角度讨论了模型的可扩展性。所提出的模型提供了一个语义标签系统，用于应用数据驱动的方法来解码无处不在的地图图像，这也为信息和通信技术时代地图学理论的发展铺平了道路。