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Expressing Data

Mon/Wed 4:00pm - 5:30pm 

Course Description

Human beings are producing, consuming and sharing data at any given moment. However, what kinds of data are meaningful to us? How do we capture and collect that data? What are the best ways to present it? What stories do we want to tell with data? This course will explore these questions and more. Students will learn basic techniques for data collection and filtering. Student projects can be digital, physical, visual, musical, or (with approval) take any form imagined.
Prerequisite: Interaction Lab


Learning Objectives

 * Students will understand data compositions behind objects.
 * Students will learn basic technologies of capturing and visualizing data.
 * Students will explore online data through APIs.


Assignments

There are 4 assignments and 1 final project in this course. In the first 4 weeks, students will capture one data series per week, sketch out the data in paper as Monday assignment; learn some related computer technology, and sketch out the same data in code as Wednesday assignment.
 * Week 1: Capture data about stuff you eat or drink in text
 * Week 2: Take photos about people or things you see
 * Week 3: Record audios about sound you listen
 * Week 4: Track locations about places you go

From week 5 to week 7, students will learn technologies related to larger dataset and work on their final projects.


Readings

'The Visual Display of Quantitative Information' by Edward Tufte
 * Chapter 4 ( Page 90 - 105 )
 * Chapter 6 ( Page 122 - 137 )
 * Chapter 9 ( Page 176 - 191 )

'Envisioning information' by Edward Tufte
 * Chapter 3 ( Page 52 - 65 )
 * Chapter 5 ( Page 80 - 95 )


Grading

Grades will be determined based on the following breakdown:
 * 20% Attendance & Participation
 * 60% Assignments & Exercises
 * 20% Final Project


Attendance

Attendance in all classes is mandatory. Unexcused absences and tardiness will effect your grade. Please let me know ahead of time so that I can help you determine how to make up the material. Cellphones not permitted in class.


Weekly Breakdown

 * Week 1
   * Introduction, Text Visualization Inspirations, Data Formats
   * Charts, Color, Shape and Typography in Data Visualization
 * Week 2
   * Assignments Review, Image Visualization Inspirations, Image Capture
   * Image Process and Visualization Techniques
 * Week 3
   * Assignments Review, Audio Visualization Inspirations, Audio Capture
   * Audio Process and Visualization Techniques
 * Week 4
   * Assignments Review, Location Visualization Inspirations, Location Capture
   * Location Data Process and Visualization Techniques
 * Week 5
   * Assignments Review, Using APIs
   * Workshop
 * Week 6
   * Collecting and Filtering Data
   * Workshop
 * Week 7
   * Workshops
   * Final Projects


Links

http://feltron.com
http://dear-data.com/
http://dataphys.org/list/