Data Visualization Principles, Concepts & Best Practices (Part I)

Recording, part 1
Recording, part 2
Github repo with notes, code and data

The DSI’s Winter 2019 workshop series focuses on Data Visualization, from principles and best practices to implementation with various technologies. Attendance at all sessions is recommended as concepts and materials build throughout the quarter. All workshops will be recorded and links will be posted here shortly after their conclusion. Learners are recommended to watch any missed workshops to best prepare for subsequent sessions.

Statistical graphics play a key role in research, from exploring data to communicating results. But, how do you identify what plots to use and when to use them? In this workshop we’ll discuss the governing principles of data visualization, the roles of graphics in the data research life cycle, and how to compose and reason about different types of plots.

This two-part workshop taught by Professor Duncan Temple Lang and Dr. Pamela Reynolds will focus on theory and application featuring case studies to teach best practices for constructing and evaluating plots – including your own! If you have a plot you’d like to improve, submit it to datascience@ucdavis.edu with a brief description of the problem (message you are trying to convey, your audience, and the nature of your data). We’ll give you feedback and might feature your example during the workshop!

After this two-part workshop learners should be able to:

• Describe the roles of statistical graphics for research
• Utilize the grammar of graphics to reason about how to improve data storytelling
• Identify and construct the appropriate plot(s) for a given question and dataset
• Compare the features and utility of different plot types
• Effectively use graphical elements (color, annotations, aesthetics, line types, etc.) to improve plots
• Implement best practices to maximize the impact of graphical displays

The last 30 minutes of this workshop are open for individual Q&A.

Prerequisites & Target audience:

This workshop is aimed at researchers (students, postdoctoral scholars, faculty, staff) who are working with data and using graphics for exploratory analyses and scholarly communication (i.e., publications). Learners are encouraged to bring printouts of static graphics they would like to improve. Laptops are not necessary for this workshop.