Handle URI:
http://hdl.handle.net/10754/600177
Title:
Visualizing Summary Statistics and Uncertainty
Authors:
Potter, K.; Kniss, J.; Riesenfeld, R.; Johnson, C.R.
Abstract:
The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.
Citation:
Potter K, Kniss J, Riesenfeld R, Johnson CR (2010) Visualizing Summary Statistics and Uncertainty. Computer Graphics Forum 29: 823–832. Available: http://dx.doi.org/10.1111/j.1467-8659.2009.01677.x.
Publisher:
Wiley-Blackwell
Journal:
Computer Graphics Forum
KAUST Grant Number:
KUS-C1-016-04
Issue Date:
12-Aug-2010
DOI:
10.1111/j.1467-8659.2009.01677.x
Type:
Article
ISSN:
0167-7055
Sponsors:
Thanks to Samuel Gerber for providing clustering expertise and code. This work was funded in part by the DOE SciDAC Visualization and Analytics Center for Enabling Technologies (www.vacet.org), NIH NCRR Grant No. 5P41RR012553-10 and KAUST (KUS-C1-016-04).
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorPotter, K.en
dc.contributor.authorKniss, J.en
dc.contributor.authorRiesenfeld, R.en
dc.contributor.authorJohnson, C.R.en
dc.date.accessioned2016-02-28T06:44:28Zen
dc.date.available2016-02-28T06:44:28Zen
dc.date.issued2010-08-12en
dc.identifier.citationPotter K, Kniss J, Riesenfeld R, Johnson CR (2010) Visualizing Summary Statistics and Uncertainty. Computer Graphics Forum 29: 823–832. Available: http://dx.doi.org/10.1111/j.1467-8659.2009.01677.x.en
dc.identifier.issn0167-7055en
dc.identifier.doi10.1111/j.1467-8659.2009.01677.xen
dc.identifier.urihttp://hdl.handle.net/10754/600177en
dc.description.abstractThe graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.en
dc.description.sponsorshipThanks to Samuel Gerber for providing clustering expertise and code. This work was funded in part by the DOE SciDAC Visualization and Analytics Center for Enabling Technologies (www.vacet.org), NIH NCRR Grant No. 5P41RR012553-10 and KAUST (KUS-C1-016-04).en
dc.publisherWiley-Blackwellen
dc.subjectI.3.6 [Computer Graphics]: Methodology and Techniquesen
dc.titleVisualizing Summary Statistics and Uncertaintyen
dc.typeArticleen
dc.identifier.journalComputer Graphics Forumen
dc.contributor.institutionUniversity of Utah, Salt Lake City, United Statesen
dc.contributor.institutionUniversity of New Mexico, Albuquerque, United Statesen
kaust.grant.numberKUS-C1-016-04en
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