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Linked Micromap: Exploratory Data Analysis and Geographic Visualization of Spatial Statistics Data

Minho Kim 1

1상명대학교

Accredited

ABSTRACT

Graphic elements, e.g., bar and histogram, have been widely utilized as a tool of information visualization for the exploratory data analysis (EDA) of spatial statistics data. Meanwhile, conventional thematic map such as choropleth and flow maps has been considered to be an efficient visualization method in discovering the spatial distribution and pattern of georeferenced statistics data. However, the interest of linked micromap (LM), first proposed in statistics academia, is being grown as an useful method for EDA recently. This research implemented the LM with R programming language in order to visualize spatial statistics data information of Seoul Metropolitan City, and it provided some results of LM implementation. In addition, this study evaluated the distinct features of LM in comparison with conventional thematic maps. LM-based visualization is anticipated to gather more interests in many academic fields due to it’s functional ability to minimize information loss of spatial statistics data.

Citation status

* References for papers published after 2022 are currently being built.