Ours is a data-rich world with more information than ever freely available for analysis, scrutiny and consumption. Likewise, the tools and techniques for visualizing that information are robust. As a result, data visualization has permeated nearly every sector of our society, from traditional newsrooms and strategic communication firms, to corporate agencies and universities.
Effective data visualizations transform numbers and concepts into relatable shapes, colors and concrete structures, making the abstract easier to digest and understand. The best visualizations are intuitively consumed, at a glance, without much thought. As a result, they often redirect a viewer’s focus from comprehending what they see to analyzing the data considering its implications, and discovering its insights.
As the fields of statistics, design and storytelling continue to converge, transforming data into engaging visualizations that promote exploration and understanding is an important service. However, effective data visualization is predicated on several principles and techniques. This chapter examines how to connect with your audience by making data accessible and consumable. To get there, we will unpack how to find, understand, organize and prepare data in sophisticated and interactive information displays. We will also consider tips for minimizing intimidation factor associated with data.
Finding data: It is true that we have access to more data than ever before, providing an uncomfortable number of opportunities for storytelling that deepens our understanding of complex topics. However, finding data on a specific topic or issue isn’t always easy. First, it’s important to start with credible sources. It’s your job to scrutinize the data, looking for any suspicious statements, comparisons or figures. Using a few simple strategies can making using online databases and search engines relatively easy. Ultimately, the best advice for an aspiring data journalist is to be tenacious and not give up too easily.
Understanding data: Working with data can be intimidating. Big data sets are often comprised of millions of numbers, collected over many years, and divided into several different categories. For example, crime data for a single city like Chicago is accumulated over decades and often categorized by location, type, severity and time of day. Rather than feel intimidated, try approaching datasets like you would any human source. Ask it questions. Scrutinize the answers. Pose you questions from a number of different angles. Data visualization isn’t just about turning a collection of numbers into a chart. It’s about making a connection between the data and the story that data tells.
Exploring data: When your story begins with a dataset it will be up to you to analyze the data in search of interesting stories and insights. To do this, you many need to engage in some data mining and statistical analysis. Data mining is the process of discovering patterns, trends and relationships in large datasets. You ultimate goal is to extract the information you need from a dataset and transform it into an understandable structure.
Choosing the right visual display: The brain’s ability to understand visual images as metaphors for more complex ideas is nothing short of astounding. Choosing the right visual display for your information begins with a clear understanding of the information and good judgment about the best way to display it. Today, there are an uncountable number of ways you can structure and design visualization. But choices about chart, type, style, typography and color should always be dictated by the information.