InfoGuides: Data Visualization: Guides

Data Visualization Guides

Below is a list of data visualization (data viz) guides selected by DDSS staff.

Guidance hub: Data Visualization (UK Government)
- Tips and suggestions for Tables, Charts, Maps, and the use of Color.
- Other presentations of the same / similar content:
  - Sequence, some in powerpoint: Data visualization e-learning
  - Older, in pdf: Effective Charts and Tables in Official Statistics
- Style guide, based on best practices: Data Visualization Service Manual
Data Visualization Toolkit (DaSy Center for IDEA)
- Good overview of many visualization types, considerations (including Accessibility) and engagement, with links to many more resources and tools.
Visualizing Data
- from DATA + DESIGN: A simple introduction to preparing and visualizing information.
- By Infoactive and the Donald W. Reynolds Journalism Institute.

Data + Design: A Simple Introduction to Preparing and Visualizing Information by Trina Chiasson, Dyanna Gregory, et al. Trina Chiasson, Dyanna Gregory and Over 50 people worked hard over the course of many months to create this book, which we’re delighted to offer as a free resource. If you do use or build upon this work, make sure to give credit to the contributors who made it happen by including a link to infoactive.co/data-design. This book is licensed under Creative Commons, BY-NC-SA. We would love for you to build upon, remix, and improve upon this work for non-commercial projects.
Call Number: Available ONLINE CC-BY-NC-SA

Chart Dos and Don'ts - Angela Zoss Duke
Ten Guidelines for Effective Data Visualization in Scientific Publications - This article from researchers in Environmental Science is a straightforward guide for data display in any field.
Ten Simple Rules for Better Figures - This article rom researchers in Computational Biology gives useful examples of the principles.

Fundamentals of Data Visualization by Claus Wilke Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book's visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story
Call Number: Available ONLINE through Mason/O'Reilly AND through the Author's Website
ISBN: 9781492031086
Publication Date: 2019-05-14

Chicago Guide to Writing about Numbers
- Creating effective tables and charts (mp4) - Recorded lecture based on the book
- Organizing data in tables and charts (mp4) - Recorded lecture based on the book
Creating Data Literate Students (edited book, free online)
- Chapter 6: Making Sense of Data Visualization (Justin Joque) - How aspects of visualizations represent data
- Chapter 7: Data presentation: Showcasing your data with charts and graphs (Tierney Steelberg) - Overview of different chart types and what questions each can answer.

Noah Illinsky - Purpose > Content > Structure > Formatting
- Choosing visual properties for successful visualizations pdf
  Visual properties include position, shpae, size, color and others. See a summary
Ben Fry - Acquire > Parse > Filter > Mine > Represent > Refine > Interact
- Computational Information Design pdf

See also software-specific courses that cover data visualization (e.g., R, Python, Tableau, Excel).

Data Visualization (University of Illinois) through Coursera.- free to audit

Information Visualization (Indiana University)

L inkedIn Learning offers several tutorials and courses on Data Visualization.

Picking the Right Chart for Your Data (1.3hrs Beginner)
Data Visualization: Best Practices (1.25hrs, Beginner)
Learning Data Visualization (3.75 hrs, Beginner)
Data Visualization: Storytelling (1.5hrs, Intermediate)
Data Visualization for Data Analysts (1.5 hrs, Beginner) - already familiar with data analysis
Learning Data Science: Tell Stories With Data (1.3hrs, Appropriate for All)
Data Visualization Tips and Tricks (2.24hrs, Intermediate)
See also videos for specific software, like Tableau, Excel, R, and Python.