By Topic

Worm plots

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Matthews, G. ; Dept. of Comput. Sci., Western Washington Univ., Bellingham, WA, USA ; Roze, M.

Scientists sometimes spend hours conducting experiments only to find that the resulting data proves difficult to analyze with traditional visualization techniques. A typical laboratory experiment, for example, will setup several systems in each of two or more groups-a control group and various treatment groups. The investigator will then measure various parameters for each system over time (sometimes dozens to hundreds of parameters). The investigator tries to answer this question: What is different between the control and treatment groups? Field monitoring of polluted and unpolluted sites within a region result in the same kinds of data and the same difficulties in visualization. Plotting multiple lines on a single 2D plot quickly gets confusing. Plus, the dynamic interactions between parameters can be hard to see. 3D visualizations help researchers make qualitative insights about data more easily. We developed a 3D plotting technique, called “worm plots”, for visualizing these kinds of data. Our visualization tool examines how groups of points change over time. If we plot circles for each time slice, then these circles will change their relative sizes and positions as time goes by. To visualize these evolving dynamics, we connect these time slices with conic sections. This gives us spacetime worms that can be displayed graphically. In our experience, these simple circular cross sections work best when exploring data. They can be rendered quickly and give an easily intuited summary of each group. Further enhancements tend to make the image busy and difficult to interpret

Published in:

Computer Graphics and Applications, IEEE  (Volume:17 ,  Issue: 6 )