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Interactive Data Exploration for Geoscience

dc.contributor.authorBeilschmidt, Christian
dc.contributor.authorDrönner, Johannes
dc.contributor.authorMattig, Michael
dc.contributor.authorSchmidt, Marco
dc.contributor.authorAuthmann, Christian
dc.contributor.authorNiamir, Aidin
dc.contributor.authorHickler, Thomas
dc.contributor.authorSeeger, Bernhard
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-21T11:24:36Z
dc.date.available2017-06-21T11:24:36Z
dc.date.issued2017
dc.description.abstractData-driven research requires interactive systems supporting fast and intuitive data ex- ploration. An important component is the user interface that facilitates this process. In biodiversity research, data is commonly of spatio-temporal nature. This poses unique opportunities for visual analytics approaches. In this paper we present the core concepts of the web-based front end of our VAT (Visualization, Analysis and Transformation) system, a distributed geo-processing application. We present the results of a user study and highlight unique features for the management of time and the generalization of data.en
dc.identifier.isbn978-3-88579-660-2
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-266
dc.subjectVisualization
dc.subjectBiodiversity
dc.subjectScientific Workflows
dc.titleInteractive Data Exploration for Geoscienceen
dc.typeText/Conference Paper
gi.citation.endPage126
gi.citation.publisherPlaceBonn
gi.citation.startPage117
gi.conference.date6.-10. März 2017
gi.conference.locationStuttgart
gi.conference.sessiontitleWorkshop Big (and small) Data in Science and Humanities (BigDS17)

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