2009•Geography and Geo-Information ScienceRequires access

Concept,Characteristics and Advances of Geographic Knowledge Visualization

Gong Jianhua

Open publisher page 1 citations

Abstract

As a new field of visualization,knowledge visualization is to use maps,graphics or images to construct and transfer insights and knowledge between at least two persons.In view of geovisualization,geographic diagram,geoinformatic Tupu,and visual analytics are cutting edge researches on visual and graphic representation and discovery of geographic knowledge.Thus,this paper focuses on the discussion of geographic knowledge visualization in terms of general knowledge visualization and geographic diagram.In the paper,the concept and characteristics of geographic knowledge visualization are mainly explored according to the dual coding theory of representation of mental images and spatial thinking in mental images.Based on the theoretical foundation mentioned above,five formats of geographic knowledge visualization are introduced.Besides geographic knowledge map,they are concept maps,mind maps,cognitive maps,semantic networks and thinking maps.In the end,the practical application of geographic knowledge visualization and its development trend in the fields of geographic knowledge maps' construction,geographic collaborative work,design and implementation of visualization model and related algorithms,and so forth are summarized.

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What this paper is about

As a new field of visualization,knowledge visualization is to use maps,graphics or images to construct and transfer insights and knowledge between at least two persons.In view of geovisualization,geographic diagram,geoinformatic Tupu,and visual analytics are cutting edge researches on visual and graphic representation and discovery of geographic knowledge.Thus,this paper focuses on the discussion of geographic knowledge visualization in terms of general knowledge visualization and geographic diagram.In the paper,the concept and characteristics of geographic knowledge visualization are mainly explored according to the dual coding theory of representation of mental images and spatial thinking in mental images.Based on the theoretical foundation mentioned above,five formats of geographic knowledge visualization are introduced.Besides geographic knowledge map,they are concept maps,mind maps,cognitive maps,semantic networks and thinking maps.In the end,the practical application of geographic knowledge visualization and its development trend in the fields of geographic knowledge maps' construction,geographic collaborative work,design and implementation of visualization model and related algorithms,and so forth are summarized.

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Available abstract

As a new field of visualization,knowledge visualization is to use maps,graphics or images to construct and transfer insights and knowledge between at least two persons.In view of geovisualization,geographic diagram,geoinformatic Tupu,and visual analytics are cutting edge researches on visual and graphic representation and discovery of geographic knowledge.Thus,this paper focuses on the discussion of geographic knowledge visualization in terms of general knowledge visualization and geographic diagram.In the paper,the concept and characteristics of geographic knowledge visualization are mainly explored according to the dual coding theory of representation of mental images and spatial thinking in mental images.Based on the theoretical foundation mentioned above,five formats of geographic knowledge visualization are introduced.Besides geographic knowledge map,they are concept maps,mind maps,cognitive maps,semantic networks and thinking maps.In the end,the practical application of geographic knowledge visualization and its development trend in the fields of geographic knowledge maps' construction,geographic collaborative work,design and implementation of visualization model and related algorithms,and so forth are summarized.

Key concepts: Geovisualization, Visualization, Visual analytics, Computer science, Information visualization, Geographic information system, Data science, Knowledge representation and reasoning

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