An Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity Hardware

Beilschmidt, ChristianMattig, MichaelFober, ThomasSeeger, BernhardDavid, KlausGeihs, KurtLange, MartinStumme, Gerd2019-08-272019-08-272019978-3-88579-688-6https://dl.gi.de/handle/20.500.12116/24982The exploratory and interactive visualization of big spatial data is becoming increasingly important in business, science, and many other application areas. In this paper, we discuss the Circle Merging Quadtree, an efficient method for aggregating and visualizing big spatial point data on commodity hardware.enData VisualizationBiodiversity Data AnalyticsBig Spatial Data AnalysisAn Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity HardwareText/Conference Paper10.18420/inf2019_341617-5468