Exploring Data Visualization

Presentation at Elon Student Undergraduate Research Forum, Spring 2011

Andrew Sutherland  (Dr. Shanon Duvall) Department of Computing Sciences

Recently huge amounts of data have become available for anyone to use and interpret. The question is how to manage, interpret, and gain knowledge from all this data. Observing raw data tells very little about trends or patterns, and almost nothing can be inferred without the use of intelligent, informing visualizations.

I will be exploring a wide variety of these visualizations. My work will create a library of data visualizations that satisfy the following requirements: the library can be widely applied to the vast multitudes of free online data; someone with little or no programming experience can use the library to create intelligent, informing visualizations; and the code will show good coding and documentation conventions as well as ways to create new, unique visualizations. These requirements will ensure reusability and extensibility for future Data Visualization needs at Elon University and beyond.

Throughout the process of creating this library, I will be exploring the factors that produce a good visualization by going through the process of creating them: finding data, choosing the best visualization for it, and tweaking the code to create the most informative visualization. I will be using a language called Processing. Processing is built on top of Java with an emphasis on graphics and animation. It greatly simplifies all the coding that needs to be done to produce good drawings, so that most of the work in creating visualizations is in finding good data and exploring what type of visualization best summarizes it. In my talk I will demonstrate the new software system I created, discuss the successful use of it in a current Elon class, and give ideas for future work in this exciting area.