Publikation: The Gridfit Algorithm : An Efficient and Effective Approach to Visualizing Large Amounts of Spatial Data
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Link zur Lizenz
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
In a large number of applications, data is collected and referenced by their spatial location. Visualizing large amounts of spatially referenced data on a limited-size display often results in poor visualizations due to the high degree of overplotting of neighboring data points. In this paper, we introduce a new approach to visualizing large amounts of spatially referenced data. The basic idea is to intelligently use the unoccupied pixels of the display instead of overplotting data points. After formally describing the problem, we present two solutions which are based on (1) placing overlapping data points on the nearest unoccupied pixel and (2) shifting data points along a screen-filling curve (e.g., Hilbert-curve). We then develop a more sophisticated approach called Gridfit, which is based on a hierarchical partitioning of the data space. We evaluate all three approaches with respect to their efficiency and effectiveness, and show the superiority of the Gridfit approach. For measuring the effectiveness, in addition to comparing the resulting visualizations we introduce mathematical effectiveness criteria measuring properties of the generated visualizations such as distance- and positionpreservation.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
KEIM, Daniel A., Annemarie HERRMANN, 1998. The Gridfit Algorithm : An Efficient and Effective Approach to Visualizing Large Amounts of Spatial Data. Visualization '98. Research Triangle Park, NC, USA. In: Proceedings Visualization '98 (Cat. No.98CB36276). IEEE, 1998, pp. 181-188,. ISBN 0-8186-9176-X. Available under: doi: 10.1109/VISUAL.1998.745301BibTex
@inproceedings{Keim1998Gridf-5904, year={1998}, doi={10.1109/VISUAL.1998.745301}, title={The Gridfit Algorithm : An Efficient and Effective Approach to Visualizing Large Amounts of Spatial Data}, isbn={0-8186-9176-X}, publisher={IEEE}, booktitle={Proceedings Visualization '98 (Cat. No.98CB36276)}, pages={181--188,}, author={Keim, Daniel A. and Herrmann, Annemarie} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/5904"> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5904/1/The_Gridfit_Algorithm.pdf"/> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5904"/> <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5904/1/The_Gridfit_Algorithm.pdf"/> <foaf:homepage rdf:resource="http://localhost:8080/"/> <dc:creator>Keim, Daniel A.</dc:creator> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dcterms:issued>1998</dcterms:issued> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T16:01:17Z</dcterms:available> <dcterms:bibliographicCitation>First publ. in (rev. version): Proceedings Visualization '98, October 18 - 23, 1998, Research Triangle Park, North Carolina / Ed. by David Ebert ... New York: Association for Computing Machinery, 1998, pp. 181-188</dcterms:bibliographicCitation> <dc:contributor>Herrmann, Annemarie</dc:contributor> <dcterms:title>The Gridfit Algorithm : An Efficient and Effective Approach to Visualizing Large Amounts of Spatial Data</dcterms:title> <dc:language>eng</dc:language> <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T16:01:17Z</dc:date> <dcterms:abstract xml:lang="eng">In a large number of applications, data is collected and referenced by their spatial location. Visualizing large amounts of spatially referenced data on a limited-size display often results in poor visualizations due to the high degree of overplotting of neighboring data points. In this paper, we introduce a new approach to visualizing large amounts of spatially referenced data. The basic idea is to intelligently use the unoccupied pixels of the display instead of overplotting data points. After formally describing the problem, we present two solutions which are based on (1) placing overlapping data points on the nearest unoccupied pixel and (2) shifting data points along a screen-filling curve (e.g., Hilbert-curve). We then develop a more sophisticated approach called Gridfit, which is based on a hierarchical partitioning of the data space. We evaluate all three approaches with respect to their efficiency and effectiveness, and show the superiority of the Gridfit approach. For measuring the effectiveness, in addition to comparing the resulting visualizations we introduce mathematical effectiveness criteria measuring properties of the generated visualizations such as distance- and positionpreservation.</dcterms:abstract> <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights> <dc:format>application/pdf</dc:format> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:creator>Herrmann, Annemarie</dc:creator> </rdf:Description> </rdf:RDF>