| Week | Date | Topic (lecture) | Date | Topic (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 |
- Time & Location
- Monday 4pm-5:15pm, Informatics West 107 (Lecture)
Wednesday 4pm-5:15pm, Informatics West 109 (Lab)
First meeting: Monday, Aug. 25th, 2014
- Instructor
- Yong-Yeol Ahn (call me YY)
yyahn@indiana.edu
Office: Informatics East Room 316
Phone: (812) 856 2920
Office hours: Tuesday 3pm-5pm, or by appointment
(email me or use MeetMe)
- AI
- Vikas Rao Pejaver
vpejaver@imail.iu.edu
Office hours: TBD (Lindley Hall LH 310), Wednesday 5:15pm-6:15pm (Info West 109)
- Announcements
- All announcements will be sent through the course mailing list. Please check your email at least once a day.
- Textbook
- Tamara Munzner, Visualization
Analysis and Design (Draft version)
- Scott Murray, Interactive Data Visualization for the Web [Amazon]
- Programming
- We will learn basics of Javascript and D3.js to create visualizations and play
with them.
- Prerequisites
- 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.
Description
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.
Objectives
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
- All announcements will be sent via email. You are responsible for
reading each announcement in detail.
- You are expected to read all reading assignments prior to the
class.
- You have the responsibility of backing up all their data and
code. Today is International
Backup Awareness Day! Use a backup drive, Dropbox, Google drive, or whatever
service you find it useful. I highly recommend using a version
control system, especially with hosting services such as github (IU provides a firewalled github), bitbucket, etc.
- Please contact the instructor if you have a disability that
require some arrangements so that appropriate arrangements can be
made. For more information: check http://studentaffairs.iub.edu/dss/
- Any reasonable absence, if notified 24 hours prior to the
absence, will not get any penalty. Reasonable excuses include: religious
observances, job interviews, illness, etc.
- If you have any issues, don't hesistate to contact me or IU's
Counseling and Psychological Services.
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
- Attendance & Class participation 20%
- Project: 40%
- Assignments: 40%