Research On Metaphorical Expression Of Hierarchical Semantic Information In River System Map

Massive data has been produced with the penetration and popularization of Internet and big data,the huge,abstract and heterogeneous nature of data hinders the cognition of it,and data visualization is an effective way to solve this problem.However,conventional data visualizations mostly do not introduce spatial perspective,without the establishment of information perception space similar to the real world,thus they fail to mobilize users' spatial cognitive ability fully and are not competent for complex data visualization tasks.As a special visual expression form,map expresses natural things and social phenomena according to scientific laws,modeling the real world,can trigger users' sense of space naturally and convey geographic information effectively.Inspired by this,metaphorical map,as an innovative and cross data visualization method,takes map as the expression carrier of non-spatial data,represents semantic target with map elements,maps abstract data to the virtual space,and users are able to recognize data by reading the map,which can make full use of the innate spatial cognitive talent and acquired spatial life experience of human beings,thus it can offset the flaws of conventional data visualization methods in terms of spatialization.The proportion of non-spatial semantic information can not be ignored in all kinds of information,and hierarchical semantic information is one of the most important and common categories,which describes the organizational structure of nested things.As a basic geographical element,river system has a natural branch-mainstream intersection hierarchy.Based on the structural similarity between the two,this study aims at the metaphorical expression of hierarchical semantic information in river system map,focusing on the automatic construction of virtual river system.The main contents include : hierarchical tree is used to model hierarchical semantic information,the semantic relationship in the data is described based on the ontology,the entity and relationship in raw data are mapped graphically,and the attribute and structure information are organized in a unified way.According to the horizontal and vertical characteristics,hierarchical data is classified as flat,balanced and deep type.The data foundation for the generation of metaphor map is established by this;Bezier curve and random noise curve are used to simulate the virtual river,and the virtual river system is constructed automatically based on the structural features ofparallel,feathery and converging river systems.Graphic support for spatial associative cognition is provided by this;The mapping relationship between hierarchical semantic information and virtual river system is established,the former is the ontology,and the latter is the metaphor.The attribute information is expressed metaphorically by the length,line width,line type and other characteristics of river symbols,and the topological relationship of specific river systems is the metaphorical expression of structural information.And the complete path of information transmission is realized by this.For theory and method verification,this study selects book catalogue,the confirmed count of novel coronavirus pneumonia in China's provinces and cities,and the organization of project documents,as the representative data of balanced,flat and deep hierarchical semantic information.The experiments are performed on feathered,parallel and convergent river system maps,practicality and aesthetics are presented in the result.This study utilizes virtual river system to express and analyze hierarchical semantic information visually for the first time,the proposed river system metaphor map can stimulate users' spatial cognitive ability and interest naturally,express the structural information of hierarchical data effectively,and support the development of hidden laws and knowledge.Moreover,it explores more possibilities of the theory and method of data visualization,expands the types of metaphorical map and further proves its value.However,dynamic visualization of time series data is not supported,which will be supplemented in subsequent studies.