Visual analytics : how much visualization and how much analytics?

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KEIM, Daniel, Florian MANSMANN, Jim THOMAS, 2009. Visual analytics : how much visualization and how much analytics?. In: SIGKDD Explorations. 11(2), pp. 5-8. Available under: doi: 10.1145/1809400.1809403

@article{Keim2009Visua-17491, title={Visual analytics : how much visualization and how much analytics?}, year={2009}, doi={10.1145/1809400.1809403}, number={2}, volume={11}, journal={SIGKDD Explorations}, pages={5--8}, author={Keim, Daniel and Mansmann, Florian and Thomas, Jim} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:rights rdf:resource=""/> <dc:creator>Thomas, Jim</dc:creator> <dc:contributor>Mansmann, Florian</dc:contributor> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dspace:hasBitstream rdf:resource=""/> <dc:date rdf:datatype="">2012-01-31T13:17:50Z</dc:date> <dc:rights>terms-of-use</dc:rights> <dc:contributor>Keim, Daniel</dc:contributor> <dc:creator>Keim, Daniel</dc:creator> <dcterms:title>Visual analytics : how much visualization and how much analytics?</dcterms:title> <dcterms:bibliographicCitation>First publ. in: SIGKDD Explorations ; 11 (2009), 2. - pp. 5-8</dcterms:bibliographicCitation> <bibo:uri rdf:resource=""/> <dcterms:issued>2009</dcterms:issued> <dcterms:available rdf:datatype="">2012-01-31T13:17:50Z</dcterms:available> <dcterms:isPartOf rdf:resource=""/> <dc:creator>Mansmann, Florian</dc:creator> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:language>eng</dc:language> <dc:contributor>Thomas, Jim</dc:contributor> <dcterms:abstract xml:lang="eng">The term Visual Analytics has been around for almost five years by now, but still there are on-going discussions about what it actually is and in particular what is new about it. The core of our view on Visual Analytics is the new enabling and accessible analytic reasoning interactions supported by the combination of automated and visual analysis. In this paper, we outline the scope of Visual Analytics using two problem and three methodological classes in order to work out the need for and purpose of Visual Analytics. By examples of analytic reasoning interaction, the respective advantages and disadvantages of automated and visual analysis methods are explained leading to a glimpse into the future of how Visual Analytics methods will enable us to go beyond what is possible when separately using the two methods.</dcterms:abstract> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:hasPart rdf:resource=""/> </rdf:Description> </rdf:RDF>

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