WeekDateTopic (lecture)DateTopic (lab)
1 8/25 Intro / Administrivia 8/27 Lab introduction
2 9/1 No school (Labor day) 9/3 HTML / CSS
3 9/8 Intro / History 9/10 Javascript - 1
4 9/15 Lilly Library visit 9/17 Javascript - 2 / A#1
5 9/22 Perception 9/24 SVG
6 9/29 (YY will be traveling) Design 10/1 D3
7 10/6 Data / proposal due 10/8 Drawing with data
8 10/13 Fundamental Visualizations 10/15 Drawing with Data - 2
9 10/20 (YY will be traveling) Fundmeantal visualizations - 2 10/22 Texts
10 10/27 Texts / Project update due 10/29 Maps - 1
11 11/3 Maps - 1 11/5 Maps - 2
12 11/10 Maps - 2 11/12 Graphs and Trees - 1
13 11/17 Graphs and Trees - 1 / Project update due 11/19 Graphs and Trees - 2
14 11/24 Thanksgiving 11/26 Thanksgiving
15 12/1 Graphs and Trees - 2 12/3 TBD
16 12/8 Final project presentation 12/10 Final project presentation

Basic Information

Time & Location
Monday 4pm-5:15pm, Informatics West 107 (Lecture)
Wednesday 4pm-5:15pm, Informatics West 109 (Lab)

First meeting: Monday, Aug. 25th, 2014
Yong-Yeol Ahn (call me YY)
Office: Informatics East Room 316
Phone: (812) 856 2920
Office hours: Tuesday 3pm-5pm, or by appointment (email me or use MeetMe)
Vikas Rao Pejaver
Office hours: TBD (Lindley Hall LH 310), Wednesday 5:15pm-6:15pm (Info West 109)
All announcements will be sent through the course mailing list. Please check your email at least once a day.
Tamara Munzner, Visualization Analysis and Design (Draft version)
Scott Murray, Interactive Data Visualization for the Web [Amazon]
We will learn basics of Javascript and D3.js to create visualizations and play with them.

This course is open to graduate students as well as advanced undergraduate students. There is no formal requirements, but it is recommended to have programming background (I210 & I211 or equivalent). Also I308: "Information Representation" is a recommended class before taking this class. Working knowledge of Javascript and scripting languages (e.g. Python) will be helpful. Contact the instructor if you are uncertain about your background.


From dashboards in a car to cutting-edge scientific papers, we extensively use visual representation of data. As our world becomes increasingly connected and digitized, and as more decisions are being driven by data, data visualization is becoming a critical skill for every knowledge worker. In this course we will learn fundamentals of data visualization and create visualizations that can provide insights into complex datasets.


By the end of the course, you will be able to evaluate data visualizations based on the understanding of the principles of visualization, types of data, and the strengths and limitations of an array of visualization techniques. You will be able to explore datasets using visualizations and create explanatory visualizations.

Final assessement

The final assessment is based on a team project. Your team will choose a visualization problem, e.g. "I want to visualize this data" or "I want to find a way to visualize this type of data". The former, data-driven question mainly aims to combine existing visualization techniques to effectively convey your messages while the latter, method-driven question mainly aims to develop a new way to visualize particular types of data. There is no clear cut between them and it is fine to be creative. :)


Class policies

Academic integrity

The principles of academic honesty and ethics will be enforced. Any cases of academic misconduct (cheating, fabrication, plagiarism, etc) will be thoroughly investigated and immediately reported to the School and the Dean of Students. You should actively discuss with others, but you should write your own report. Credit all the sources (discussion with other students, used softwares, etc).

Grading policy