Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Linking and Brushing

  • Matthew O. Ward
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_1129

Synonyms

Linked brushing; Linked views

Definition

Within the context of visual data exploration, Linking refers to the process in which user interactions in one display of a multi-display system are applied to some or all other displays. In this same context, brushing consists of the interactive selection of a subset of the displayed data by either dragging the mouse over the data of interest or using a bounding shape to isolate this subset. Together, linked brushing is one of the most powerful interactive tools for doing exploratory data analysis using visualization.

Historical Background

Perhaps the earliest reference to linked brushing was by McDonald [10] as a mechanism for cross-referencing between multiple plots. The term brushing was introduced in 1978 by Newton [11], who defined it as an interactive method for painting a group of points with a square, circular, or polygonal brush. Since then, researchers have expanded on these concepts, as described in the next section.

Foundations...

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Recommended Reading

  1. 1.
    Becker RA, Cleveland WS. Brushing scatterplots. Technometrics. 1987;29(2):127–42.MathSciNetCrossRefGoogle Scholar
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    Becker RA, Cleveland WS, Wilks AR. The use of brushing and rotation for data analysis. In: Cleveland WS, McGill ME, editors. Dynamic graphics for statistics. Pacific Grove: Wadsworth; 1988. p. 1–50.Google Scholar
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    Chen H. Compound brushing. In: Proceedings of IEEE Symposium Information Visualization; 2003. p. 181–8.Google Scholar
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    Cook D, Swayne DF. Interactive and dynamic graphics for data analysis with R and Ggobi. New York: Springer; 2008.zbMATHGoogle Scholar
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    Doleisch H, Hauser H. Smooth brushing for focus+context visualization of simulation data in 3D. J WSCG. 2002;10(1):147–55.Google Scholar
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    Fua Y-H, Ward MO, Rundensteiner EA. Structure-based brushes: a mechanism for navigating hierarchically organized data and information spaces. IEEE Trans Vis Comput Graph. 2000;6(2):150–9.CrossRefGoogle Scholar
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    Hauser H, Ledermann F, Doleisch H. Angular brushing of extended parallel coordinates. In: Proceedings of the IEEE Symposium on Information Visualization; 2002. p. 127–30.Google Scholar
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    Henze C. Feature detection in linked derived spaces. In: Proceedings of the Conference on Visualization; 1998. p. 87–94.Google Scholar
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    Martin AR, Ward MO. High do dimensional brushing for interactive exploration of multivariate data. In: Proceedings of IEEE Conference on Visualization; 1995. p. 271–8.Google Scholar
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    McDonald JA. Orion I: interactive graphics for data analysis. Technical report, Stanford University. 1983.Google Scholar
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    Newton C. Graphica: from alpha to omega in data analysis. In: Wang P, editor. Graphical representation of multivariate data. New York: Academic; 1978. p. 59–92.CrossRefGoogle Scholar
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    Wills GJ. 524,288 ways to say "this is interesting." In: Proceedings of the IEEE Symposium on Information Visualization; 1996. p. 54–60.Google Scholar
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    Xie Z, Ward MO, Rundensteiner EA, Huang S. Integrating data and quality space interactions in exploratory visualizations. In: Proceedings of the International Conference on Coordinated and Multiple Views in Exploratory Visualization; 2007. p. 47–60.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Worcester Polytechnic InstituteWorcesterUSA

Section editors and affiliations

  • Daniel A. Keim
    • 1
  1. 1.Computer Science DepartmentUniversity of KonstanzKonstanzGermany