Data visualization is a tool that can be used in many ways. As you've seen while building examples throughout the book, data visualization is sometimes used to communicate information in a novel or interesting way; sometimes data visualization provides clarity, other times it's just used to make cool things.

Regardless of whether you're a journalist wanting to highlight a change in GDP, a scientist needing to communicate the results of an experiment, or a software engineer looking to integrate visualization into a product, chances are that you'll want data visualization that is clear, concise, and does not mislead. Although the examples in this chapter will mainly be from a news media context, many of the points we'll discuss apply similarly to data visualization in general.

In this chapter, we'll look at a few general principles to keep in mind while building data visualizations and I'll give some examples of good data visualization as well. Note that I'm in no way a data visualization expert per se; I'm a developer and a journalist with a degree of learned design experience, and my thoughts on what constitute good data visualization are very much influenced by my background in building explanatory data-driven graphics for titles such as The Financial Times, The Times, The Economist, and The Guardian. These are very fast-paced newsrooms, and the goal is generally to communicate the important bits of a dataset to an audience instead of letting them explore the data. Although you might not have the same demands in your use of D3 as that of a visual journalist, much of what I'll be discussing also applies if you're using D3 in Academia, Publishing, or elsewhere; the skill of being able to quickly and succinctly communicate information is incredibly valuable, no matter your profession.

That caveat out of the way, let's go on with discussing a few of the finer points of what exactly comprises good data visualization.