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Information Visualization : Scope, Techniques and Opportunities for Geovisualization

Information Visualization : Scope, Techniques and Opportunities for Geovisualization

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KEIM, Daniel A., Christian PANSE, Mike SIPS, 2004. Information Visualization : Scope, Techniques and Opportunities for Geovisualization. In: DYKES, J., ed. and others. Exploring Geovisualization. Oxford:Elsevier, pp. 1-17

@incollection{Keim2004Infor-5420, title={Information Visualization : Scope, Techniques and Opportunities for Geovisualization}, year={2004}, address={Oxford}, publisher={Elsevier}, booktitle={Exploring Geovisualization}, pages={1--17}, editor={Dykes, J.}, author={Keim, Daniel A. and Panse, Christian and Sips, Mike} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/5420"> <dcterms:title>Information Visualization : Scope, Techniques and Opportunities for Geovisualization</dcterms:title> <dcterms:bibliographicCitation>First publ. in: Exploring Geovisualization / J. Dykes ... (eds.). Oxford: Elsevier, 2004, pp. 1-17</dcterms:bibliographicCitation> <dcterms:issued>2004</dcterms:issued> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:14Z</dc:date> <dc:contributor>Keim, Daniel A.</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5420"/> <dcterms:abstract xml:lang="eng">Never before in history has data been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data has become increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques that have been developed over the last two decades to support the exploration of large data sets. In this article, we provide an overview of information visualization and visual data mining techniques, and illustrate them using a few examples. We show that an application of information visualization methods provides new ways of analyzing geography related data.</dcterms:abstract> <dc:contributor>Sips, Mike</dc:contributor> <dc:creator>Sips, Mike</dc:creator> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:14Z</dcterms:available> <dc:rights>deposit-license</dc:rights> <dc:format>application/pdf</dc:format> <dc:language>eng</dc:language> <dc:creator>Keim, Daniel A.</dc:creator> <dc:creator>Panse, Christian</dc:creator> <dc:contributor>Panse, Christian</dc:contributor> <dcterms:rights rdf:resource="https://creativecommons.org/licenses/by-nc-nd/2.0/legalcode"/> </rdf:Description> </rdf:RDF>

Dateiabrufe seit 01.10.2014 (Informationen über die Zugriffsstatistik)

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