Department of Computer Science and Engineering
Yonsei University
Mon at 1:00 - 3:00pm & Wed at 2:00 - 3:00pm
D408
Prof. Minsuk Kahng
Assistant Professor, Department of Computer Science and Engineering
E-mail: [email protected]
Website: https://minsuk.com
How can we help people make sense of large datasets and discover insights? Data visualization is a powerful tool widely used to analyze complex datasets, communicate findings, and support decision-making. This course introduces its principles and techniques, focusing on transforming various types of raw data into effective visual representations and applying interactive techniques to explore data from diverse perspectives. Students will gain hands-on experience building interactive data visualizations using JavaScript frameworks, through in-class exercises and a term project with real-world data.
어떻게 하면 사람들이 방대한 데이터를 쉽게 이해하고 흥미로운 통찰(insights)을 얻을 수 있을까? 데이터 시각화는 복잡한 데이터를 분석하고, 효과적으로 전달하며, 의사결정을 돕는 강력한 도구입니다. 이 과목에서는 데이터 시각화의 기본 개념인 여러 형태의 데이터를 시각적으로 표현하는 방법(visual representation)과 사용자가 데이터를 다양한 관점에서 탐색할 수 있도록 돕는 상호작용(interaction) 기법을 배웁니다. 또한, 수업에서 진행하는 간단한 실습과 실제 데이터를 활용한 학기 프로젝트를 통해 JavaScript로 직접 인터랙티브 시각화를 구현합니다.
This course will be taught in Korean.
At the completion of this course, students will:
| Week | Topic | Assignments |
|---|---|---|
| 1 | Course Introduction | * Pre-Course Survey |
| Data Abstraction | ||
| 2 | Fundamental Graphs | * HW 1: Visualiation Design |
| Graphical Encodings (1) | ||
| 3 | Graphical Encodings (2) | |
| Exploratory Data Analysis and Tableau | * HW 2: Exploratory Data Analysis | |
| 4 | Rule of Thumb, Tufte's Principles, Pie Charts | |
| Perception and Color | ||
| 5 | Programming (1): HTML/CSS and SVG | |
| Programming (2): JavaScript Frameworks and React | ||
| 6 | Programming (3): Vega-Lite and D3.js | * Projects: Proposals |
| Interaction (1) | ||
| 7 | Interaction (2) | |
| Multi-Dimensional Data | ||
| 8 | Mid-Term Exam | |
| 9 | High-Dimensional Data | * HW 3: Programming for Interactive Visualization |
| Projects: Proposals | ||
| 10 | Text and Documents | |
| Human-Centered Design Process and Prototyping | * Projects: Posters with Prototyping | |
| 11 | Hierarchical and Network Data | |
| Projects: Posters | ||
| 12 | Geographical Data | |
| Evaluation | * Projects: Final Presentations | |
| Guest Lecture (1) | ||
| 13 | Guest Lecture (2) | |
| Projects: Final Presentations (1) | ||
| 14 | Projects: Final Presentations (2) | |
| Projects: Final Presentations (3) | ||
| 15 | Final Exam |
Your performance will be evaluated via exams, individual assignments, team projects, and participation. The distribution of grading will be as follow (subject to change):
By the end of the term, your team will develop a web application that visualizes large-scale real world data, as a final product of your group project. It will likely be a single-page web application that runs on web browsers, written in JavaScript based on what you will learn from lab sessions. To help you learn how to implement such a web-based visualization tool, we will have lab sessions and an individual programming assignment.
The team receives one grade for the group project. However, allocation of the grade among team members will in some cases not be equal, if team members do not contribute relatively equally to the effort. It will be calibrated based on project feedback and evaluation form around the end of the term.
There will be several in-class activities. Starting in Week 3, there will be lab sessions on programming. Students will be expected to complete programming exercises and submit them during class. They can discuss with peers and freely ask questions to the instructor during class. In order to work on these activities, students are expected to bring their own laptop to class.
Many announcements will be made during in-person class meetings.
We use LearnUs for additional announcements, assignment submissions, grading, etc.
We use GitHub Classroom for managing all the programming assignments.
This website will be used only for syllabus. For up-to-date information (e.g., schedule), please check LearnUs.
배성재
This course is designed based on a number of visualization courses offered in other universities. Below I list some of them. I especially thank Professors Enrico Bertini and Jeffrey Heer for sharing their materials with me.