An Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity Hardware
dc.contributor.author | Beilschmidt, Christian | |
dc.contributor.author | Mattig, Michael | |
dc.contributor.author | Fober, Thomas | |
dc.contributor.author | Seeger, Bernhard | |
dc.contributor.editor | David, Klaus | |
dc.contributor.editor | Geihs, Kurt | |
dc.contributor.editor | Lange, Martin | |
dc.contributor.editor | Stumme, Gerd | |
dc.date.accessioned | 2019-08-27T12:55:23Z | |
dc.date.available | 2019-08-27T12:55:23Z | |
dc.date.issued | 2019 | |
dc.description.abstract | The 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.identifier.doi | 10.18420/inf2019_34 | |
dc.identifier.isbn | 978-3-88579-688-6 | |
dc.identifier.pissn | 1617-5468 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/24982 | |
dc.language.iso | en | |
dc.publisher | Gesellschaft für Informatik e.V. | |
dc.relation.ispartof | INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft | |
dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-294 | |
dc.subject | Data Visualization | |
dc.subject | Biodiversity Data Analytics | |
dc.subject | Big Spatial Data Analysis | |
dc.title | An Efficient Method for Exploratory Data Visualization of Big Spatial Data on Commodity Hardware | en |
dc.type | Text/Conference Paper | |
gi.citation.endPage | 262 | |
gi.citation.publisherPlace | Bonn | |
gi.citation.startPage | 261 | |
gi.conference.date | 23.-26. September 2019 | |
gi.conference.location | Kassel | |
gi.conference.sessiontitle | Data Science |
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