Zur Kurzanzeige

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

dc.contributor.authorBeilschmidt, Christian
dc.contributor.authorMattig, Michael
dc.contributor.authorFober, Thomas
dc.contributor.authorSeeger, Bernhard
dc.contributor.editorDavid, Klaus
dc.contributor.editorGeihs, Kurt
dc.contributor.editorLange, Martin
dc.contributor.editorStumme, Gerd
dc.date.accessioned2019-08-27T12:55:23Z
dc.date.available2019-08-27T12:55:23Z
dc.date.issued2019
dc.identifier.isbn978-3-88579-688-6
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/24982
dc.description.abstractThe 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.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofINFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-294
dc.subjectData Visualization
dc.subjectBiodiversity Data Analytics
dc.subjectBig Spatial Data Analysis
dc.titleAn Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity Hardwareen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages261-262
mci.conference.sessiontitleData Science
mci.conference.locationKassel
mci.conference.date23.-26. September 2019
dc.identifier.doi10.18420/inf2019_34


Dateien zu dieser Ressource

Thumbnail
Name:
paper3_11.pdf
Größe:
130.0Kb
Format:
PDF
Öffnen

Zur Kurzanzeige