Why Teach with Visualizations

Initial Publication Date: March 27, 2006

Visualizations are intimately connected with all phases of model development and analysis. At the beginning level, visualizations can be used to help develop conceptual models of how things work. As one moves up the modeling hierarchy, visualizations are extremely useful for conveying the behavior and characteristics of more sophisticated mathematical and statistical models.

  • Arguably, graphical visualization is the most efficient method for qualitative interpretation of data sets or model performance.
  • Visualizations present massive amounts of information to help scientists identify relevant patterns and processes in nature. Many science courses would be incomplete without the ability to understanding these graphical representations.
  • Not only are visualizations omnipresent throughout the sciences but they are commonly used to present quantitative information in such disciplines as demographics, economics, and medicine. Thus, exposing students to the use and analysis of visualizations is an important aspect of their overall education today.

Examples of when visualizations are useful to geoscientists include:

  • Many interactive web based data sites are available that allow visitors to select and view different science data. These are great resources for students and faculty interested in the specific data sets available at a given interactive visualization site.
  • Visualization software allows one to generate images and animations from mathematical functions or from your own data or data sets of your choice. These packages also often include some data and/or image manipulation capabilities. Although our primary focus here is more sophisticated visualization models, several examples of simple graphics programs will be given in the software section as alternatives to the spreadsheet environment.
  • Visualizations of output from mathematical or statistical models is one of the best ways to convey model behavior for large complex models, e.g. for visualization of results from a general circulation model of the ocean or atmosphere. Our discussion focuses on visualizing the results of experiments from complex models that have been performed by established scientific research groups as opposed to visualizing results from models that can be readily manipulated and run by students. Examples of visualizing output from simpler mathematical or statistical models that students can easily experiment with can be found in the examples section along with the individual model description.