ECS 163 — Information Visualization

The ability to effectively explore, analyze, and explain data is paramount in the era of computing and big data. This course will delve into the art and science of information visualization and interface design, tailored for diverse and complex data landscapes encountered in daily activities. The lectures will cover design principles of human-computer interaction, offer a comprehensive exploration of data visualization techniques, and provide authentic practices (e.g., in-class activities, homework assignments, and course projects) for implementing and evaluating interactive visualization systems. The goal is to empower students with the skills to combat information overload and engage a broader audience in analytic thinking through compelling visual representations.

Starting in Spring 2024, the course previously titled Information Interfaces has been formally renamed to Information Visualization.

Course Learning Objectives

By the end of this course, you are expected to:

  1. Gain a comprehensive understanding of fundamental data visualization techniques and theories.
  2. Develop the ability to create, assess, and provide constructive criticism for various visualization designs.
  3. Acquire hands-on experience in building interactive data visualizations using D3.js.
  4. Harness your skills to create a visualization dashboard for explorative data analysis or compelling storytelling.
  5. Engage with current research in the field of visualization through reading and discussing visualization research papers.

Lecture Information

Lecture Time: 5:10 - 6:00 PM Mondays, Wednesdays and Fridays

Location: OLSON 006 (Discussion Session is at OLSON 206)

Instructor: Dongyu Liu, Kemper 2123

Instructor Office Hours: To Be Announced (location: Kemper 2123)

Teaching Assistant: Yueqiao (Christina) Chen (yeqchen@ucdavis.edu), Shicheng Wen (scwen@ucdavis.edu)

TA Office Hours: To Be Announced (one hour per TA starting week 2) [Zoom Link]

GitHub Repository for Programming Assignments https://github.com/via-teaching/ecs163-25s

Textbook: There is no textbook, but you may find these two books helpful for this class:

  1. Visualization Analysis and Design, Tamara Munzner, A K Peters/CRC Press, December 2014 (UC e-Resources)
  2. Interactive Data Visualization for the Web, 2nd Edition. Scott Murray, O’Reilly Press. (UC e-Resources, code example)

Additional Tutorials: Check Recourses Page

Announcements and Discussion Piazza (Canvas Integrated)

We use Piazza for announcements, Q&A, discussion, and project team formation. Piazza is more structured and searchable than email or chat, and everyone is required to join. The course staff will check Piazza regularly, and all class-related questions should be asked there. We encourage active participation by posting and answering questions—this is the fastest way to get help with homework. If you would like your question to be seen only by the instructor and/or TAs, please use the private post option. Make sure your notification settings are turned on so you do not miss important updates.

TA office hours will take place through Piazza’s Live Q&A feature, where TAs will respond to questions in real time within the thread. Zoom may be used when a live conversation is necessary, but should be reserved for cases where Piazza is not sufficient.

Grading Breakdown:

    HW Assignment 0            3%

    HW Assignment 1            6%

    HW Assignment 2          12%

    HW Assignment 3          18%

    Reading Reports             10%

    Final Project                    45%

    Class Participation            6%    (Workshops 3 * 1% + Project Proposal Presentations 3 * 2%)

Bonus: There will be a total of 7 discussion sessions. If you attend 6 or more sessions, you will receive 2 bonus points toward your final course grade. If you attend at least 4 sessions, you will receive 1 bonus point.

All homework and project DUE dates are at 11:55 PM PST.

SCHEDULE (Evolving!!)

DUE For marking any deadlines

PROJECT For marking any project-relevant tasks

ASSIGNED For marking any homework assignments

READING For marking reading tasks

Week 1: March 31 — Introduction

Mon 3/31 Lecture: Course Introduction
  • Course Content and Learning Goals
  • Course Logistics

READING Visualization Analysis & Design, Tamara Munzner, CRC Press, 2014 [UC e-resources]: Chapter 1, What's VIS, and Why Do it (1.1 — 1.xx), Chapter 2, What: Data Abstraction (xx — xx).
Tue 4/1 No Discussion
Wed 4/2 Lecture: Introduction to Data Visualization
  • Definition of Visualization
  • The Value of Visualization (Record, Analyze, Communicate)
Fri 4/4 Lecture: Data, Marks, and Channels I
  • Sketching the Data Graph
  • Data Definition, Dataset Types, Data Attributes

ASSIGNED HW0 (Sketching Visualizations)

Week 2: April 7 — Visual Encoding

Mon 4/7 Lecture: Data, Marks, and Channels II
  • Visualization Design Process
  • Marks, Channels, and Visual Encodings

READING Visualization Analysis & Design, Tamara Munzner, CRC Press, 2014 [UC e-resources]: Chapter 5, Marks and Channels (xx — xx) Chapter 6, Rules of Thumb (xx — xx)
Tue 4/8 Discussion: Visualization Programming Overview + Reading Discussion (Yueqiao, Shicheng)

DUE Week 1 Reading Report  (11:55pm, PST)
Wed 4/9 Lecture: Effective Visual Encoding I
  • Guidelines to Use Visual Channels (Expressiveness and Effectiveness)
  • Perception Accuracy
Fri 4/11 Lecture: Effective Visual Encoding II
  • Using Space (In)effectively
  • (De-)Obfuscating
  • (Mis)leading the Witness

DUE HW0 (11:55pm, PST)

PROJECT Start to find your team members

Week 3: April 14 — Perception Theory

Mon 4/14 Lecture: Graphical Perception I
  • Discriminability, Separability, and Popout

READING Visualization Analysis & Design, Tamara Munzner, CRC Press, 2014 [UC e-resources]: Chapter 10, Map Color and Other Channels (xx — xx)
Tue 4/15 Discussion: Reading Discussion (Yueqiao, Shicheng)

DUE Week 2 Reading Report  (11:55pm, PST)
Wed 4/16 Lecture: Graphical Perception II + Color I
  • Gestalt Principles
  • Color and Color Space
Fri 4/18 Lecture: Color II
  • Color in Visualization (label, measure, represent, enliven)
  • Color Harmonization

Week 4: April 21 — Implementation

Mon 4/21 Workshop: Web (HTML/CSS/JS) Programming (Shicheng, Yueqiao) 

READING Visualization Analysis & Design, Tamara Munzner, CRC Press, 2014 [UC e-resources]: Chapter 12, Facet Into Multiple Views (xx — xx) Chapter 13, Reduce Items and Attributes (xx — xx)

ASSIGNED HW1 (Static Visualizations)
Tue 4/22 Discussion: HW1 Details + Reading Discussion (Yueqiao, Shicheng)

DUE Week 3 Reading Report  (11:55pm, PST)
Wed 4/23 Workshop: Introduction to D3.js (Shicheng, Yueqiao)
Fri 4/25 Workshop: D3 Interactions & Animations (Shicheng, Yueqiao)

PROJECT DUE Form project teams

Week 5: April 28 — Visual Navigation

Mon 4/28 Lecture: Interaction Design

READING Subjectivity in personal storytelling with visualization. Information Design Journal. S. Carpendale, A. Thudt, C. Perin, and W. Willett.  IEEE Transactions on Visualization and Computer Graphics 23(1):48-64 (2017). [pdf ] OR More Than Telling a Story: Transforming Data into Visually Shared Stories. B. Lee, N. H. Riche, P. Isenberg and S. Carpendale. IEEE Computer Graphics and Applications 35(5):84-90 (2015) [pdf]
Tue 4/29 Discussion: Final project details, examples, + Reading Discussion. (Yueqiao, Shicheng)

DUE Week 4 Reading Report  (11:55pm, PST)
Wed 4/30 Lecture: Narrative Visualization

DUE HW1 (11:55pm, PST)

ASSIGNED HW2 (Visualization Dashboard: Layout Design + Visual Encoding)
Fri 5/2 Lecture: Animation

Week 6: May 5 — Proposal Presentations

Mon 5/5 PROJECT Project Proposal Presentation Session I
Tue 5/6 No Discussion 
Wed 5/7 PROJECT Project Proposal Presentation Session II
Fri 5/9 PROJECT Project Proposal Presentation Session III

Week 7: May 12 — Visualization Techniques

Mon 5/12 Lecture: Tabular Data I
  • Visualization Techniques for Tabular Data
  • Advanced Techniques for Multivariate Data

PROJECT DUE Project Proposal Report
Tue 5/13 Discussion: TBD + Reading Discussion. (Yueqiao, Shicheng)

DUE Week 5 Reading Report  (11:55pm, PST)
Wed 5/14 Lecture: Tabular Data II + Temporal Data I
  • Dimension Reduction
  • Modeling Time
  • Visual Analysis Tasks for Temporal Data

DUE HW2 (11:55pm, PST)

ASSIGNED HW3 (Visualization Dashboard: Interactivity)
Fri 5/16 Lecture: Temporal Data II
  • Visualization Techniques for Time-varying Data

Week 8: May 19 — Visualization Techniques

Mon 5/19 Lecture: Mapping & Cartography
  • Spatial Data and Map Visualization
  • Spatial + Temporal
Tue 5/20 Discussion: TBD. (Yueqiao, Shicheng)
Wed 5/21 Lecture: Graph and Network Visualization I
  • Graphs/Networks in Real Life
  • Graph Definition and Tasks
Fri 5/23 Lecture: Graph and Network Visualization II
  • Graph Visualization Techniques (Node-link, Matrix, Trees)
  • Handling Large Graph

DUE HW3 (11:55pm, PST)

Week 9: May 26 — Evaluation

Mon 5/26 Lecture: Evaluation I
  • What is Visualization Evaluation, and why is it needed?
  • Controlled Experiments (Formal User Study)

PROJECT DUE Project Progress Report
Tue 5/27 Discussion: TBD. (Yueqiao, Shicheng)
Wed 5/28 Lecture: Evaluation II
  • Informal User Study, Case Study, and Usability Study
Fri 5/30 Lecture: Presentation Styles

Week 10:  June 2 — TBD

Mon 6/2 Lecture: TBD
Tue 6/3 No Discussion
Wed 6/4 Lecture: TBD

INSTRUCTION END

 

About Curiosity:

"The important thing is not to stop questioning. Curiosity has its own reason for existing. One cannot help but be in awe when he contemplates the mysteries of eternity, of life, of the marvelous structure of reality. It is enough if one tries merely to comprehend a little of this mystery every day."
— Albert Einstein