Data Visualization - Winter 2019
Instructor: Amit Chourasia, San Diego Supercomputer Center, UCSD
Teaching assistant: Sumit Binani, Computer Science and Engineering, UCSD
Textbook Visualization Analysis and Design, Tamara Munzner (A K Peters Visualization Series, CRC Press, 2014)
Day 0 Jan 4, Day 1 Jan 5, Day 2 Jan 19 , Day 3 Feb 2 , Day 4 Feb 16 , Day 5 Mar 2 , Day 6 - Finals Mar 16
Class schedule
Day 0 supplement (Jan 4)
Afternoon (3pm - 6:30pm)
Tutorial by TA (Optional attendance, but strongly recommended)
- HTML & CSS
- Javascript
- D3JS
- Download tutorial material See Lecture notes section.
Day 1 (Jan 5)
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
- Readings: Chapter 4
- Exercise 2
- Start developing final project proposal : identify dataset, create tasks
Day 2 (Jan 19)
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.
- Colors suppliment
- Tables
- 11-noon DSE Guest lecture
Afternoon
- Network and Trees
- Tutorial (TA): Tableau
- Exercise 2 using Tableau (Time permitting)
Home work
- Reading - Chapter 10 (Map color and other channels)
- Exercise 3 & Exercise 4
- Final project proposal
Day 3 (Feb 2)
Morning
- Manipulate View
- Facets
- Reduction
- Design discussion and logistics
- Network X and Bokeh tutorial (TA)
Afternoon
- Final project proposal presentations (By students) Presentation order
Home work
Day 4 (Feb 16)
Morning
- Focus and Context
- Spatial data
- Case study presentations (By students) - Presentation order
Afternoon
- Case study presentations (By students) - Presentation order
Home work
Day 5 (Mar 2)
Morning
- Scientific visualization methods
- Tools demo / tutorial - VisIt software (Amit)
- VisIt (Download Visit 2.9.2 not 2.10)
- Download Sample data ~200 mb. Unzip and move to your Desktop.
- Download Comet host file. Unzip and move this file to ~/.visit/hosts (on linux, mac) or ~/Documents/VisIt/hosts (on windows)
- Visit CSV to Binary Example
Afternoon
-
1:00pm Guest lecture - Scaling and benchmarking web based visualization Dr. David Nadeau, Sr. Scientist, San Diego Supercomputer Center, UCSD.
Abstract: Traditional plots work well to show detail and short trends when data is small. But as data grows larger, plot visual complexity and drawing times increase. New visual designs are needed to clearly show complex data, and new high performance techniques are needed to draw visualizations quickly. This talk introduces issues in high performance visualization, GPUs, OpenGL, and WebGL, and illustrates them using large 3D graph and volume visualizations.
-
In class exercise
Home work
Day 6 - Final exam (Mar 16)
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
- ~ 65% - Exercises
- ~ 5% - Final project proposal
- ~ 30% - Final project
Class policy
- Attendance is mandatory
- Must complete all exercises
- Must complete final project
Guest Lecturers
- Applying Color Theory to Visualization - Thersa-Marie Rhyne, Computer Graphics and Visualization Consultant