NDLI: Recursive pattern: a technique for visualizing very large amounts of data

Content Provider	IEEE Xplore Digital Library
Author	Keim, D.A. Kriegel, H.-P. Ankerst, M.
Copyright Year	1995
Description	Author affiliation: Inst. for Comput. Sci., Munchen Univ., Germany (Keim, D.A.; Kriegel, H.-P.; Ankerst, M.)
Abstract	An important goal of visualization technology is to support the exploration and analysis of very large amounts of data. In this paper, we propose a new visualization technique called a 'recursive pattern', which has been developed for visualizing large amounts of multidimensional data. The technique is based on a generic recursive scheme which generalizes a wide range of pixel-oriented arrangements for displaying large data sets. By instantiating the technique with adequate data- and application-dependent parameters, the user may greatly influence the structure of the resulting visualizations. Since the technique uses one pixel for presenting each data value, the amount of data which can be displayed is only limited by the resolution of current display technology and by the limitations of human perceptibility. Beside describing the basic idea of the 'recursive pattern' technique, we provide several examples of useful parameter settings for the various recursion levels. We further show that our 'recursive pattern' technique is particularly advantageous for the large class of data sets which have a natural order according to one dimension (e.g. time series data). We demonstrate the usefulness of our technique by using a stock market application.
Starting Page	279
Ending Page	286
File Size	1763481
Page Count	8
File Format	PDF
ISBN	0818671874
ISSN	10702385
DOI	10.1109/VISUAL.1995.485140
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-10-29
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data visualization Humans Multidimensional systems Computer science Pattern analysis Displays Stock markets Visual databases Decision making Automation
Content Type	Text
Resource Type	Article

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2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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