Data Visualization - Winter 2020

Instructor: Amit Chourasia, San Diego Supercomputer Center, UCSD

Teaching assistant: Kishore P. Venkatswammy Reddy, Computer Science and Engineering, UCSD

Textbook Visualization Analysis and Design, Tamara Munzner (A K Peters Visualization Series, CRC Press, 2014)


Day 1 Jan 3, Day 1-supp Jan 3, Day 2 Jan 17 , Day 3 Jan 31 , Day 4 Feb 14 , Day 5 Feb 28 , Day 6 - Finals Mar 13


Class schedule

Day 1 (Jan 3)

Morning

  • Course structure and introductions
  • Visualization overview and Motivation
  • Discussion
  • Review of key visualizations
  • Exercise 1 (no coding)
  • Abstraction

Afternoon

  • Marks and Channels
  • Rules of thumb
  • Exercise 2 (Time permitting)

Home work

Day 1 supplement (Jan 4)

Afternoon (2:15pm - 5:30pm)

Tutorial by TA (Optional attendance, but strongly recommended)


Day 2 (Jan 17)

Morning

  • Guest Lecture - Applying Color Theory to Visualization. Thersa-Marie Rhyne, Computer Graphics and Visualization Consultant.

    Abstract: We provide an overview of the fundamentals of color theory and approaches to formulating your own colorization guide for visualization content creation Our journey includes the introduction to the concepts of color models and harmony, a review of color vision principles, the defining of color gamut, spaces and systems and demonstrating online and mobile apps for performing color analyses of digital media. Freely available commercial and research tools for your continued use in color selection and color deficiency assessments are highlighted.

  • Tutorial (TA): Tableau
  • 11:30am-12:30pm DSE Guest lecture

Afternoon

  • Colors suppliment
  • Tables
  • Network and Trees
  • Exercise 2 using Tableau (Time permitting)

Home work


Day 3 (Jan 31)

Morning

  • Manipulate View
  • Facets
  • Reduction
  • Design discussion and logistics
  • Network X and Bokeh tutorial (TA)
  • 11:30am-12:30pm DSE Guest lecture

    Afternoon

  • Final project proposal presentations (By students) Presentation order

Home work


Day 4 (Feb 14)

Morning

  • Focus and Context
  • Spatial data
  • Case study presentations (By students) - Presentation order
  • 11:30am-12:30pm DSE Guest lecture (Tentative)

    Afternoon

  • Case study presentations (By students) - Presentation order

Home work


Day 5 (Feb 28)

Morning

Afternoon

  • Guest Lecture (TBD)
  • In class exercise

Home work


Day 6 - Final exam (Mar 13)

Student presentations : Final project presentations


Course Grading

- A (Excellent 4.0) >= 90% - B (Good 3.0) >= 80% - C (Fair 2.0) >= 70% - D (Barely passing 1.0) >= 60% - F (Fail) < 60%

Grade calculation will be as follows

Class policy

  • Attendance is mandatory
  • Must complete all exercises
  • Must complete final project

Guest Lecturers

  1. Applying Color Theory to Visualization - Thersa-Marie Rhyne, Computer Graphics and Visualization Consultant