A Four-level Focus + Context Approach to Interactive Visual Analysis of Temporal Features in Large Scientific Data

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dc.contributor.authorMuigg, Philippen_US
dc.contributor.authorKehrer, Johannesen_US
dc.contributor.authorOeltze, Steffenen_US
dc.contributor.authorPiringer, Haralden_US
dc.contributor.authorDoleisch, Helmuten_US
dc.contributor.authorPreim, Bernharden_US
dc.contributor.authorHauser, Helwigen_US
dc.contributor.editorA. Vilanova, A. Telea, G. Scheuermann, and T. Moelleren_US
dc.date.accessioned2014-02-21T18:44:58Z
dc.date.available2014-02-21T18:44:58Z
dc.date.issued2008en_US
dc.description.abstractIn this paper we present a new approach to the interactive visual analysis of time-dependent scientific data - both from measurements as well as from computational simulation - by visualizing a scalar function over time for each of tenthousands or even millions of sample points. In order to cope with overdrawing and cluttering, we introduce a new four-level method of focus+context visualization. Based on a setting of coordinated, multiple views (with linking and brushing), we integrate three different kinds of focus and also the context in every single view. Per data item we use three values (from the unit interval each) to represent to which degree the data item is part of the respective focus level. We present a color compositing scheme which is capable of expressing all three values in a meaningful way, taking semantics and their relations amongst each other (in the context of our multiple linked view setup) into account. Furthermore, we present additional image-based postprocessing methods to enhance the visualization of large sets of function graphs, including a texture-based technique based on line integral convolution (LIC). We also propose advanced brushing techniques which are specific to the timedependent nature of the data (in order to brush patterns over time more efficiently). We demonstrate the usefulness of the new approach in the context of medical perfusion data.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume27en_US
dc.identifier.doi10.1111/j.1467-8659.2008.01207.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2008.01207.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleA Four-level Focus + Context Approach to Interactive Visual Analysis of Temporal Features in Large Scientific Dataen_US
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EuroVis08: Joint Eurographics - IEEE VGTC Symposium on Visualization