September 17, 2018 Conference paper Open Access

Kawa Nazemi; Dirk Burkhardt

DCAT Export

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        <foaf:name>Kawa Nazemi</foaf:name>
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        <foaf:name>Dirk Burkhardt</foaf:name>
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    <dct:title>JUXTAPOSING VISUAL LAYOUTS – AN APPROACH FOR SOLVING ANALYTICAL AND EXPLORATORY TASKS THROUGH ARRANGING VISUAL INTERFACES</dct:title>
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    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#gYear">2018</dct:issued>
    <dcat:keyword>Information Visualization, Visual Analytics, visual tasks, visual interfaces</dcat:keyword>
    <dct:issued rdf:datatype="http://www.w3.org/2001/XMLSchema#date">2018-09-17</dct:issued>
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    <dct:description>&lt;p&gt;Interactive visualization and visual analytics systems enables solving a variety of tasks. Starting with simple&lt;br&gt; search tasks for outliers, anomalies etc. in data to analytical comparisons, information visualizations may&lt;br&gt; lead to a faster and more precise solving of tasks. There exist a variety of methods to support users in the process&lt;br&gt; of task solving, e.g. superimposing, juxtaposing or partitioning complex visual structures. Commonly all&lt;br&gt; these methods make use of a single data source that is visualized at the same time. We propose in this paper an&lt;br&gt; approach that goes beyond the established methods and enables visualizing different databases, data-sets and&lt;br&gt; sub-sets of data with juxtaposed visual interfaces. Our approach should be seen as an expandable method. Our&lt;br&gt; main contributions are an in-depth analysis of visual task models and an approach for juxtaposing visual layouts as&lt;br&gt; visual interfaces to enable solving complex tasks.&lt;/p&gt;</dct:description>
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