Welcome to the craft of data visualization—a multidisciplinary recipe of art, science, math, technology, and many other interesting ingredients. Not too long ago we might have associated charting or graphing data as a specialist or fringe activity—it was something that scientists, engineers, and statisticians did.
Nowadays, the analysis and presentation of data is a mainstream pursuit. Yet, very few of us have been taught how to do these types of tasks well. Taste and instinct normally prove to be reliable guiding principles, but they aren't sufficient alone to effectively and efficiently navigate through all the different challenges we face and the choices we have to make.
This book offers a handy strategy guide to help you approach your data visualization work with greater know-how and increased confidence. It is a practical book structured around a proven methodology that will equip you with the knowledge, skills, and resources required to make sense of data, to find stories, and to tell stories from your data.
It will provide you with a comprehensive framework of concerns, presenting step-by-step all the things you have to think about, advising you when to think about them and guiding you through how to decide what to do about them.
Once you have worked through this book, you will be able to tackle any project—big, small, simple, complex, individual, collaborative, one-off, or regular—with an assurance that you have all the tactics and guidance needed to deliver the best results possible.
Chapter 1, The Context of Data Visualization, provides an introduction to the subject, its value and relevance today, including some foundation understanding around the theoretical and practical basis of data visualization. This chapter introduces the data visualization methodology and the step-by-step approach recommended to achieve effective and efficient designs. We finish off with a discussion about some of the fundamental design objectives that provide a valuable reference for the suitability of the choices we subsequently make.
Chapter 2, Setting the Purpose and Identifying Key Factors, launches the methodology with the first stage, which is concerned with the vital task of identifying the purpose of your visualization—what is its reason for existing and what is its intended effect? We will look closely at the definition of a visualization's function and its tone in order to shape our design decision-making at the earliest possible opportunity. To complete this scoping stage we will identify and assess the impact of other key factors that will have an effect on your project. We will pay particularly close attention to the skills, knowledge, and general capabilities that are necessary to accomplish an effective visualization solution.
Chapter 3, Demonstrating Editorial Focus and Learning About Your Data, looks at the intertwining issues of the data we're working with and the stories we aim to extract and present. We will look at the importance of demonstrating editorial focus around what it is we are trying to say and then work through the most time-consuming aspect of any data visualization project—the preparation of the data. To further cement the learning in this chapter, we will look at an example of how we use visualization methods to find and tell stories.
Chapter 4, Conceiving and Reasoning Visualization Design Options, takes us beyond the vital preparatory and scoping stages of the methodology and towards the design issues involved in establishing an effective visualization solution. This is arguably the focal point of the book as we look to identify all the design options we have to consider and what choices to make. We will work through this stage by forensically analyzing the anatomy of a visualization design, separating our challenge into the complementary dimensions of the representation and presentation of data.
Chapter 5, Taxonomy of Data Visualization Methods, goes hand-in-hand with the previous chapter as it explores the taxonomy of data visualization methods as defined by the primary communication purpose. Within this chapter we will see an organized collection of some of the most common chart types and graphical methods being used that will provide you with a gallery of ideas to apply to your own projects.
Chapter 6, Constructing and Evaluating Your Design Solution, concludes the methodology by focusing on the final tasks involved in constructing your solution. This chapter will outline a selection of the most common and useful software applications and programming environments. It will present some of the key issues to think about when testing, finishing, and launching a design solution as well as the important matter of evaluating the success of your project post-launch. Finally, the book comes to a close by sharing some of the best ways for you to continue to learn, develop, and refine your data visualization design skills.
As with most skills in life that are worth pursuing, to become a capable data visualization practitioner takes time, patience, and practice.
You don't need to be a gifted polymath to get the most out of this book, but ideally you should have reasonable computer skills (software and programming), have a good basis in mathematics, and statistics in particular, and have a good design instinct.
There are many other facets that will, of course, be advantageous but the most important trait is just having a natural creativity and curiosity to use data as a means of unlocking insights and communicating stories. These will be key to getting the maximum benefit from this text.
You cannot become skilled by reading this book alone, so you need to have a realistic perspective about the journey you are taking and the distance you have made already. However, by applying the techniques presented, then learning and developing from your experiences, you will enjoy a continued and successful process of improvement.
Regardless of whether you are an experienced visualizer or a rookie just starting out, this book should prove useful for anyone who is serious about wanting to optimize his or her design approach.
The intention of this book is to be something for everyone—you might be coming into data visualization as a designer and want to bolster your data skills, you might be strong analytically but want inspiration for the design side of things, you might have a great nose for a story but don't quite possess the means for handling or executing a data-driven design.
Some of you may never actually fulfill the role of a designer and might have other interests in learning about data visualization. You may be commissioning work or coordinating a project team and want to know how to successfully handle and evaluate a design process.
Hopefully, it will inform and inspire all who wish to get involved in data visualization design work regardless of role or background.
In this book, you will find a number of styles of text that distinguish between different kinds of information. Here are some examples of these styles, and an explanation of their meaning.
New terms and important words are shown in bold. Words that you see on the screen, in menus or dialog boxes for example, appear in the text like this:
"Explanatory data visualization is about conveying information to a reader in a way that is based around a specific and focused narrative."
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