The top ten information visualisation books for researchers

Communicating your work clearly in figures, tables and graphics is a key skill for an academic researcher, yet it is something that we are not formally taught to do. This is partly due to the fact that information visualisation is a vast field encompassing many techniques, graphic types and digital tools and we all have different requirements and backgrounds when it comes to creating graphics.

(This article was first posted in 2018, update coming soon)

Which type of graphic?

Many different types of graphics exist and your choice of graphic depends on what you are trying to show. When displaying quantitative data, are you showing categories, distribution, relationships, hierarchy, geospatial data or something changing over time? Or do you want your graphic to show a process or method? Or perhaps you want to create a schematic or an anatomical drawing from observation? Taking the time to explore different graphic types and to critique and evaluate existing graphics in the published literature will help to make your own graphical endeavours easier. We explore different graphic types in more detail in our Electv training course, Designing publication quality figures & graphics, which runs regularly throughout the year and participants from several fields of study discuss a wide range of graphics that they want to use.

Creating publication quality graphics can be time consuming, challenging and frustrating, but it can also be a rewarding and fascinating experience. Like many other things worth doing, it takes time to learn and practice creating figures, whether it is designing a schematic or spending time to learn new software. Ask yourself what type of data you have and what type of figures do you want to create, can you find examples in the literature?

Time & tools

The graphical representation of science has been popular since the renaissance when pioneers such as Da Vinci found that it was more effective to communicate complex concepts and findings in a graphic format, learning their highly skilled craft over many years in the best studios of the time. Fortunately, modern researchers can speed up the process by making use of the vast array of digital tools that are available to generate graphics if they invest the time required to learn them. This can bring additional challenges, as researchers have not all had the opportunity to learn the relevant software required to build the desired graphic nor do they always have the time available to learn. We will explore the different types of graphic and visualisation software in a future post. If you would like to dive deeper into the subject of data visualisation then you may want to investigate the books listed below. These books are an excellent foundation for anyone who is interested in visualising information and they are highly regarded by data scientists, academics, industry experts and many more. We have selected our top ten, listed in alphabetical order by author below, and many are available in university libraries. We hope you enjoy them!

Top 10 information visualisation books

1. The truthful art: data, charts and maps for communication

Alberto Cairo (2016)

2. Show me the numbers: designing tables and graphs to enlighten

Stephen Few (2004)

3. Information graphics: a comprehensive illustrated reference

RL Harris (1999)

4. Designing data visualizations

Noah lliinsky N & Julie Steele  (2011)

5. Data visualisation: a handbook for data driven design

Andy Kirk (2019)

6. The visual display of quantitative information 

Edward Tufte (2001)

7. Visual and statistical thinking: displays of evidence for making decisions 

Edward Tufte (1997)

8. Information visualization

Colin Ware (2004)

9. Visualize this: the flowing data guide to design, visualization & statistics 

Nathan Yau (2011)

10. Fundamentals of data visualization: a primer on making informative and compelling figures. 

C O Wilke (2019)

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