Title
Visualization of Off-Screen Data on Tablets Using Context-Providing Bar Graphs and Scatter Plots
Document Type
Conference Proceeding
Publication Date
2013
Abstract
Visualizing data on tablets is challenging due to the relatively small screen size and limited user interaction capabilities. Standard data visualization apps provide support for pinch-and-zoom and scrolling operations, but do not provide context for data that is off-screen. When exploring data on tablets, the user must be able to focus on a region of interest and quickly find interesting patterns in the data. We present visualization techniques that facilitate seamless interaction with the region of interest on a tablet using context-providing bar graphs and scatter plots. Through aggregation, fisheye-style, and overview+detail representations, we provide context to the users as they explore a region of interest. We evaluated the efficacy of our techniques with the standard, interactive bar graph and scatter plot applications on a tablet, and found that one of our bargraph visualizations - Fisheye-style Focus+Context visualization (BG2) resulted in the fewest errors, least frustration and took the least amount of time. Similarly, one of our scatter plot visualizations - User Driven Overview+Detail (SP3) - resulted in the fewest errors, least frustration and took the least amount of time. Overall, users preferred the context-providing techniques over traditional bar graphs and scatter plots, that include pinch-and-zoom and fling-based scrolling capabilities.
DOI
10.1117/12.2038456
Recommended Citation
Peter S. Games; Alark Joshi; Visualization of off-screen data on tablets using context-providing bar graphs and scatter plots. Proc. SPIE 9017, Visualization and Data Analysis 2014, 90170D (December 23, 2013); doi:10.1117/12.2038456.
Comments
Copyright 2013 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Link to publisher version: http://dx.doi.org/10.1117/12.2038456
SPIE Visualization and Data Analysis Conference, Best Paper Award, February 2014.