Author :
Matthews, Geoffrey ; Roze, Mike
Author_Institution :
Dept. of Comput. Sci., Western Washington Univ., Bellingham, WA, USA
Abstract :
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
Keywords :
data visualisation; graphs; statistical analysis; 3D plotting technique; 3D visualizations; conic sections; control group; data visualization; dynamic interactions; evolving dynamics; field monitoring; qualitative insights; rendering; spacetime worms; time slices; treatment groups; visualization techniques; visualization tool; worm plots; Algae; Computer worms; Containers; Data visualization; Fuels; Sampling methods; Scattering; Silver; Testing; Toxicology;
Journal_Title :
Computer Graphics and Applications, IEEE