The ubiquitous map is the extension and expansion of the traditional map, and it is a comprehensive expression of the ternary space of “geography-humanity- information”. It uses map language, image thinking and spatial thinking to analyze the characteristics of ternary space objects and realize the functions of information acquisition, transmission, and cognition between people and people, people and things, and things and things (Guo, Chen, Ying, Lv, & Li, 2018).

The ternary space constitutes a complex giant system. With the support of advanced observation technology, it has created a vast sea of spatiotemporal data streams and constituted a new and diverse map expression space (Ai, 2016). Facing the ternary space, the ubiquitous map breaks through the constraints of the traditional physical space, able to represent a variety of contents in a variety of ways and with new changes in many aspects compared with the traditional map, showing obvious “ubiquitous” characteristics. In this regard, scholars have given analysis and explanations from different perspectives and levels. They have proposed new concepts of “pseudo map” (Meng, 2017), “schematic map” (Liu & Li, 2016), “quasi-map” (Guo & Ying, 2017), “pan-map” (Guo, Chen, Ying, Lv, & Li, 2018), and “we-map” (Yan, Zhang, Du, Liu, Wang, & Yang, 2016). These can all be included in the concept of “ubiquitous map”. In reality, there are various specific types of ubiquitous maps that are widely used, such as: cyber maps, virtual reality maps, augmented reality maps, mixed reality maps, semantic maps, metaphor maps, exaggerated deformation maps, metro roadmaps, 3D city maps, personalized mobile maps, etc.

For the ubiquitous map, the addition of the information space expands a variety of new qualitative expressing contents, such as: network events, processes and phenomena in the virtual space; semantic information of the objects in the collective space. Compared with the traditional map’s element organization mode based on precise geographic positioning, the ubiquitous map describes and organizes ternary space objects based on the semantic location framework with richer content. On the other hand, the addition of the information space also expands more abundant means of expression for the ubiquitous map. The successive introduction of visual, auditory, tactile, temporal, spatial, virtual, and interactive variables enriches the representation forms of the ubiquitous map, and the design of its mathematical basis and symbol system is more flexible. For example, on the premise of ensuring the scientific nature of the map, its surface is no longer limited to the orthographic projection plane; it allows multiple mathematical conversion relations between the map coordinates and the geographic coordinates; it allows multiple scales to exist in the same map; and the graphic elements on it are no longer limited to vector symbols (Meng, 2017).

In essence, both ubiquitous maps and traditional maps are abstract descriptions and expressions of space supported by map synthesis, map projection and map visualization (Wang, Wang, & Tian, 2021). And they both have the ability to transmit, organize and express geographic information. The difference is that ubiquitous maps have further expansions in information dimension, granularity, hierarchy, expression and semantics against the background of spatiotemporal big data (Wang, 2017; Liu, Fang, Guo, & Gao, 2014), showing a more all-encompassing connotation and characteristics. This paper gives a summary for this in Table 1.

Location-based aggregation includes three core points that are closely related and mutually restricted: 1) It takes multi-modal and fragmented spatiotemporal ubiquitous information as the basic object it controls. 2) Its ultimate goal is to construct application scenes to meet users’ needs. 3) Its fundamental basis is the semantic location that mainly includes entity information and relation information (Qi, Wang, Wang, & Cui, 2014).

Focusing on the above three points, the task of location-based aggregation can be decomposed into three main links: element information extraction → association and fusion → scene construction. Element information extraction is to extract ubiquitous elements from the feature description of fragmented spatiotemporal ubiquitous information, as the information basis for aggregation computing. Association and fusion is the main computing link of location-based aggregation. Its main idea is to take location entities as the “condensation core”, and associate and fuse spatiotemporal ubiquitous information based on the similarity of certain features. Scene construction is the further processing and presentation of the results of association and fusion.

The ubiquitous map can be a participant of location-based aggregation, providing “information material” for aggregation computing; and it can also be a carrier of location-based aggregation, providing a “display platform” for aggregation results. According to the specific needs of users, the available element information is extracted from the map scenes of the relevant theme, and the information is organically organized according to certain association relations and aggregation rules under the “location” framework to construct map scenes that meet users’ needs.

Scenes are the link between ubiquitous maps and location-based aggregation. In this paper, the connotation of the ubiquitous map scene includes two aspects as “content scene” and “representation scene”. The former is the inner meaning and the latter is the outer expression. The two aspects are interdependent and mapped to each other, forming a systematic and organic organization of ubiquitous map information. According to the location-based aggregation mode and the ubiquitous map information characteristics, the content and representation scene information organization of ubiquitous maps can be divided into three levels as “features” ←→ “elements” ←→ “scenes” (Wang, Wang, & Tian, 2021). As the basis of the map scene, the level of “features” describes the information form and content type that can be directly extracted from the ubiquitous map, and can adapt to the interpretation, organization, association and analysis of fragmented “micro-contents”, forming a comprehensive and fine-grained description. The hierarchical construction from “features” to “elements” to “scenes” forms a systematic and complete ubiquitous map scene.

The content scene reflects the intrinsic meaning of the ubiquitous map. It is a complex with a specific structure and function formed by the interconnection and interaction of various elements in different ranges in the ternary space, including three levels of “content features” ←→ “content elements” ←→ “content scenes”:

• Level of “content features”: Content features are the basis for multi-faceted reflection and description of the content of ternary space elements. Combined with related research (Lv, Yuan, & Yu, 2017), this paper divides content features into six categories: temporal features, spatial features, geometric forms, attribute features, process features and semantic descriptions. Temporal features refer to the time nodes of the occurrence, development and demise of ternary space objects or phenomena, such as birth date and time of occurrence. Spatial features refer to the spatial nodes of the occurrence and development of ternary space objects or phenomena, such as place of occurrence, path, and scope of influence. Geometric forms refer to the composition and evolution structure of ternary space objects, such as geometric elements and shapes. Attribute features refer to the inherent properties of ternary space objects or phenomena, such as temperature and economic loss. Process features refer to the occurrence and evolution of ternary space objects or phenomena, such as temporal point and its state, time segment or behavior in the life cycle. Semantic features are ternary space features based on human cognition, such as name, type, subject and level.

• Level of “content elements”: Content elements are the abstract expression of complex things and phenomena in the ternary space based on time-space, attributes, semantics, etc., involving objects and relations between elements. For the ternary space, content elements can be divided into six basic types: time, place, person, thing, event, and phenomenon (Lv, Yu, Yuan, Luo, Zhou, Wu, et al., 2018). Each element type has independent connotation composition and meaning, and can be further subdivided according to its own characteristics. For example, the time element type can be further divided into absolute time, relative time and reference time; the person element type can be further divided into individual, group and organization. The element relation is a qualitative or quantitative relationship between elements based on space-time, geometry, attributes or semantics, mainly including temporal relation, spatial relation, attribute relation and compound relation.

• Level of “content scenes”: There are various types of content scenes including spatial distribution, spatiotemporal evolution, event development, logical connection, etc. The content scene is composed of elements and element relations. Under the location-based aggregation mode, its organization idea is to associate and fuse “supporting role” elements with the “leading role” element as the core. The “leading role” corresponds to the “location entity”, and the “supporting role” corresponds to the “element information”.

The representation scene is a visual reflection of the content scene, and mainly refers to the scene graph or 3D scene as a graph or image, including three levels of “representation features” ←→ “representation elements” ←→ “representation scenes”:

• Level of “representation features”: Representation features are the reflection of content features, and are also the basis for describing and forming representation elements. The representation features of ubiquitous maps include visual variables, auditory variables, tactile variables, time variables, spatial variables, hierarchical variables, scale variables, virtual variables, interactive variables, etc., such as shape, size, color, sound, texture, lighting, shadow, duration, rate of change, etc.

• Level of “representation elements”: Representation elements are the reflection of content elements, mainly involving map symbol objects, the relations between symbol objects and the structure of the map. Map symbols broadly cover point symbols, line symbols, polygon symbols, volume symbols, picture symbols, artistic symbols, color symbols, text annotations, node symbols, directed line symbols, etc. The relations between symbols include ordering relations, combination relations, topological relations, overlapping relations, etc. The map structure mainly includes map name, layer, legend, and map description. In the ubiquitous map, the representation forms of elements are flexible and diverse, that is, both abstract and concrete representation are allowed, and partial defaults are also allowed in the structure.

• Level of “representation scenes”: A representation scene is composed of representation elements under a specific layout, pattern, configuration and style. It is a visual display of content scenes, such as 2D or 3D map, dynamic map, hand-painted map, etc.