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A Guiding System of Visualization for Quantitative Bigdata Based on User Intention
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 Title & Authors
A Guiding System of Visualization for Quantitative Bigdata Based on User Intention
Byun, Jung Yun; Park, Young B.;
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Chart suggestion method provided by various existing data visualization tools makes chart recommendations without considering the user intention. Data visualization is not properly carried out and thus, unclear in some tools because they do not follow the segmented quantitative data classification policy. This paper provides a guideline that clearly classifies the quantitative input data and that effectively suggests charts based on user intention. The guideline is two-fold; the analysis guideline examines the quantitative data and the suggestion guideline recommends charts based on the input data type and the user intention. Following this guideline, we excluded charts in disagreement with the user intention and confirmed that the time user spends in the chart selection process has decreased.
Bigdata Visualization;Open Source Visualization Tool;Visualization for Quantitative Data;Visualization Guideline;Chart Recommendation;
 Cited by
Jock D. Mackinlay, Pat Hanrahan, and Chris Stolte, "Show me: Automatic presentation for visual analysis," Visualization and Computer Graphics, IEEE Transactions on, Vol.13, No.6, pp.1137-1144, 2007. crossref(new window)

Andy Kirk, "Data Visualization: a successful design process," Packt Publishing Ltd., 2012.

Stephen Few, "Now you see it: simple visualization techniques for quantitative analysis," Analytics Press, 2009.

Stephen Few, "Show me the numbers," Analytics Press, 2004.

Edward R. Tufte and P. R. Graves-Morris, "The visual display of quantitative information," CT: Graphics press, 1983.

Stanley Smith Stevens, "On the theory of scales of measurement," Science, New Series, Vol.103, No.2684, pp. 677-680, 1946.

Mike Bostock, D3: Data-Driven Documents [Internet],

DensityDesign Lab, RAW [Internet],

Hyungnyun Kim, "Case Study of Bigdata Visualization -Centre around the Visual Representation Form-," Journal of Integrated Design Research, Vol.13, No.4, pp.125-136, 2014. crossref(new window)

모리후지 다이치, 안티베이지안, 엔지니어를 위한 데이터 시각화 : D3.js로 배우는 데이터 시각화 이론과 12가지 사례, 김성재 옮김, 한빛 미디어, 2015.

Ben Fry, "Visualizing data: Exploring and explaining data with the processing environment," O'Reilly Media, Inc., 2007.

Munzner, Tamara. "Interactive visualization of large graphs and networks," Ph.D. dissertation, Stanford University, 2000.

Senay, Hikmet and Eve Ignatius, "Rules and principles of scientific data visualization," Institute for Information Science and Technology, Department of Electrical Engineering and Computer Science, School of Engineering and Applied Science, George Washington University, 1990.

Colin Ware, "Information visualization: perception for design," Elsevier, 2012.

Jacques Bertin, "The Semiology of Graphics," University of Wisconsin Press, 1983. (First edition 1967).

Michael Friendly, "A brief history of data visualization," Handbook of data visualization. Springer Berlin Heidelberg, pp.15-56, 2008.

Scott Murray, "Interactive data visualization for the Web," O'Reilly Media, Inc., 2013.

Severino Ribecca, The Data Visualisation Catalogue [Internet],