Library Research Guides: Data Visualization: Start Here

What Is Data Visualization?

Data visualization is the use of a visual or graphic display to communicate information. There are many different styles and varieties, and which type you choose will depend on the content that you want to communicate. Examples can range from hand drawn graphs and maps to infographics, charts, and diagrams. Use this guide to explore resources on how to visualize your data.

Introductions to Data Visualization

Data Visualization in Society by Kennedy ENGEBRETSEN
Call Number: Electronic Resource
ISBN: 9789463722902
Publication Date: 2020-04-16
This book is a contribution to the multi-disciplined and multi-faceted conversation concerning the forms, uses and roles of data visualization in society. Do data visualizations do 'good' or 'bad'? Do they promote understanding and engagement, or do they do ideological work, privileging certain views of the world over others? The contributions in the book engage with these core questions from a range of disciplinary perspectives.
Data Visualization for Dummies by Mico Yuk; Stephanie Diamond
Call Number: Electronic Resource
ISBN: 9781118502938
Publication Date: 2014-01-06
A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about it
Better data visualizations: a guide for scholars, researchers, and wonks by Schwabish, Jonathan A
Call Number: Electronic Resource
ISBN: 9780231550154
Publication Date: 2021
This book details essential strategies to create more effective data visualizations. The author walks readers through the steps of creating better graphs and how to move beyond simple line, bar, and pie charts. Through more than five hundred examples, the author demonstrates the do's and don'ts of data visualization, the principles of visual perception, and how to make subjective style decisions around a chart's design.
Data Feminism by Catherine D'Ignazio; Lauren F. Klein
Call Number: Electronic Resource
ISBN: 9780262044004
Publication Date: 2020-03-17
A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism.

How to Choose a Visualization Type

Check out the Best Practices recommended below for suggestions on choosing the best visualization for exploring, analyzing, or presenting your data. The following resources are also useful:

Wellesley Professor Jeremy Wilmer's Show My Data Data Visualization Web Apps
Steve Franconeri's Quick Reference Guide
From Data to Viz. From Data to Viz leads you to the most appropriate graph for your data. It links to the code to build it and lists common caveats you should avoid.

Best Practices

General best practices for effective data visualization:

Have a clear purpose
Choose the best chart for your data and purpose
Keep the design simple
Have clear labels, titles, and descriptions
Create an accessible design

See the sources below for more details lists and sources on best practices.

Other Data Visualization Guides

The following research guides from other institutions contain detailed information and resources. They helped inform this Wellesley research guide.