Data Visualization - Winter 2018
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 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 1 (Jan 5)
Morning
- Course structure and introductions
- Visualization overview and Motivation - Slides (PDF)
- Discussion
- Review of key visualizations - Slides (PDF)
- Exercise 1 (no coding)
- Abstraction - Slides (PDF)
Afternoon
- Marks and Channels - Slides (PDF)
- Rules of thumb - Slides (PDF)
- Exercise 2 (Time permitting)
Home work
- Readings: Chapter 4
- Exercise 2
- Start developing final project proposal : identify dataset, create tasks
Day 1 Supplement (Jan 6)
Morning (8:30am - noon)
Tutorial by TA
- HTML & CSS
- Javascript
- D3JS
- Download tutorial material
Day 2 (Jan 19)
Morning
-
Guest Lecture - Applying Color Theory to Visualization. Thersa-Marie Rhyne, Computer Graphics and Visualization Consultant. Slides (PDF)
Abstract: We examine the foundation of color theory and how these methods apply to building effective visualizations. We define color harmony and demonstrate the application of color harmony to case studies. The material presented is from my book on “Applying Color Theory to Digital Media and Visualization”.
- Colors suppliment - Slides (PDF)
- Tables - Slides (PDF)
Afternoon
- Network and Trees - Slides (PDF)
- 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
- Quiz 1
Day 3 (Feb 2)
Morning
- Manipulate View - Slides (PDF)
- Facets - Slides (PDF)
- Reduction - Slides (PDF)
- Design discussion and logistics
Afternoon
- Final project proposal presentations (By students) Presentation order
- Network X and Bokeh tutorial (TA)
Home work
Day 4 (Feb 16)
Morning
- Focus and Context Slides (PDF)
- Spatial data slides
- Peer review for Exercise 2 (in class). See review notes here
- 11am - noon: DSE290 Guest lecture
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 - High performance 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