Multi-Resolution Techniques for Visual Exploration of Large Time-Series Data

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dc.contributor.authorHao, Mingen_US
dc.contributor.authorDayal, Umeshwaren_US
dc.contributor.authorKeim, Danielen_US
dc.contributor.authorSchreck, Tobiasen_US
dc.contributor.editorK. Museth and T. Moeller and A. Ynnermanen_US
dc.date.accessioned2014-01-31T07:10:57Z
dc.date.available2014-01-31T07:10:57Z
dc.date.issued2007en_US
dc.description.abstractTime series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data sets which are difficult to visualize effectively with standard techniques given the limitations of current display devices. We propose a framework for intelligent time- and data-dependent visual aggregation of data along multiple resolution levels. This idea leads to effective visualization support for long time-series data providing both focus and context. The basic idea of the technique is that either data-dependent or application-dependent, display space is allocated in proportion to the degree of interest of data subintervals, thereby (a) guiding the user in perceiving important information, and (b) freeing required display space to visualize all the data. The automatic part of the framework can accommodate any time series analysis algorithm yielding a numeric degree of interest scale. We apply our techniques on real-world data sets, compare it with the standard visualization approach, and conclude the usefulness and scalability of the approach.en_US
dc.description.seriesinformationEurographics/ IEEE-VGTC Symposium on Visualizationen_US
dc.identifier.isbn978-3-905673-45-6en_US
dc.identifier.issn1727-5296en_US
dc.identifier.urihttps://doi.org/10.2312/VisSym/EuroVis07/027-034en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCR Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/Image Generation Display Algorithms; H.5.0 [Information Systems]: Information Interfaces and Presentation General.en_US
dc.titleMulti-Resolution Techniques for Visual Exploration of Large Time-Series Dataen_US
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EuroVis07: Joint Eurographics - IEEE VGTC Symposium on Visualization