Have you ever needed to make a chart or graph for a presentation or project? Creating a simple visual tool may appear to be an easy task, but with seemingly endless tools and options it can be difficult to display your information in a clear and visually pleasing way. In my recent class on Information Visualization, I learned about an expert, Ann K. Emery, who shares tips, tricks, and tools on how to make your charts or graphs look their best. While you should be sure to check out her Data Visualization Checklist, her blog posts detailing her process offer practical applications of that checklist.
In her post, “Transforming a Table: Four Charts and Four Different Stories,” Emery gave a “makeover” to a client’s data visualization. In this case, a nonprofit had a table of data comparing the number of families helped in two different counties over a period of months. Over the course of the post, she transforms the nonprofit’s table by using four different strategies. Each strategy presents a different way to display the data and each highlights a different facet of the data.
The four types she highlights are: table, line chart, clustered column chart, and stacked column chart. When discussing each of these types, Emery notes what kinds of changes she would make on each in order to best highlight the data the nonprofit is trying to share. How can adjusting the font or size of the title make the visualization more appealing? What colors should be chosen? When should subtitles be added? Does the legend make sense? What is the data saying in the chart selected? What needs to be changed to make the information clearer?
Throughout the post, Emery highlights the importance of making visualizations accessible, particularly in terms of both colorblindness and grayscale. She says that 10% of people are colorblind so inevitably your visualizations will be seen by people who cannot see all colors. Further, many visualizations may end up being printed or displayed in grayscale and you need to ensure that a grayscale version will still accurately portray your data. These and other accessibility considerations need to become second nature when thinking about information visualization. A pretty visualization will not be useful if all users cannot understand what you have created.
Emery also highlights problems that can pop up with certain charts. For example, a clustered column chart is essentially impossible to use in grayscale because you pair two colors that end up looking almost the same when not printed in color. She even has a whole post about the clustered column chart that describes in detail what is wrong with her least favorite chart
At the end of her post, instead of announcing which chart is best, Emery says “Your Choice of Charts Depends on Your Message.” The story you are trying to tell with the data is what determines what kind of graph should be used. For example, the table invites conversation among stakeholders. Each of the other chart styles highlights different aspects of the data. She encourages brainstorming while working with data to look at the information in multiple ways instead of assuming that one option will always work bes.
These kinds of charts, tables, and graphs that Emery discusses are essential for both the library school student and library worker. With the help of experts like Emery, you have more tools to help you carefully consider the different options available to see which type of information display would most accurately and effectively make your point. Watching the process of transforming charts and graphs into more effective versions of themselves through posts like these is great practice for creating your own visualizations and determining your own creative process.
Sarah Davis is a Bilingual Youth Librarian at a public library in Oklahoma and an MLIS student at the University of Oklahoma-Tulsa.
To read other posts in this “Visualize It” series, click here for the Visualization tag.