What this book covers
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.