Through the Research Commons, students, faculty, and staff can get assistance with:
Data visualization is a way of presenting data in a visual context. Not only can data visualization be used to communicate a large amount of information clearly and concisely, it can help you gain insight into things you would have otherwise been blind to had you only examined the raw data (ex. Ascombe's Quartet).
Because data comes in many forms and is gathered in virtually all disciplines - from population statistics in the U.S. Census, to text analysis of Shakespeare's work, to video recordings of a dance performance - data visualization can also take on various formats. Charts, graphs, timelines, tables, and box-and-whisker-plots are just some of the more recognizable ways to visualize data, but there are many more options out there for you to choose from.
There are three reasons why you should care about data visualization:
Visual properties or cues are the different ways we can encode data using things like length, angles, shapes, and hues. William Cleveland and Robert McGill have written about these encodings in their famous paper, Graphical Perception and Graphical Methods for Analyzing Data. As human beings and readers of visualizations, we decode these these visual cues/properties in order to try to understand the meaning behind a particular chart or graph.
One of the key ways we make sure our readers can decode our encodings is to use labels, legends, and keys, depending on the situation.