John Jordan, Thesis Supervisor John Jordan, Thesis Supervisor Dr. John C. Spychalski, Honors Advisor
The amount of data being collected and stored today is growing at an exponential rate. Our ability to turn this raw data into useful information and knowledge is not only key to making the collection of this data worthwhile, but also in preventing this data from having a slowing effect on communication and decision making. Currently, most literature details strengths and weaknesses of already-created visualization, but lack rules to follow as we create data visualization from the beginning. Creating a visualization requires an understanding of the data type at hand, as well as a specific purpose and audience for this data. Designing an informative data visualization also requires that we continually question possible causality until we have gathered enough data to reveal a story that the raw data would not have otherwise told.