Successful data visualization codifies information into a pleasing visual system, which can be explored, understood, and enjoyed more quickly than reading through the raw data itself. These visualizations often take the form of charts and graphs, many of which can be created easily using reusable charting libraries. Unfortunately, many of the libraries take a one size fits all approach, which forces users to wedge their data into the predefined charting molds offered. Working within arbitrary limitations of these libraries can homogenize how you think about your own data, effectively making you think in terms of visual clichés. The purpose of this workshop is to understand what makes a successful chart. We will explore a collection of JavaScript libraries for drawing with data, with the intent of creating succinct, self-explanatory graphical systems to answer questions about the comparison, composition, distribution or interrelationship in the data they present.