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Visual media are increasingly generated, manipulated, and transmitted by computers. When well designed, such displays capitalize on human facilities for processing visual information and thereby improve comprehension, memory, inference, and decision making. Yet the digital tools for transforming data into visualizations still require low-level interaction by skilled human designers. As a result, producing effective visualizations can take hours or days and consume considerable human effort.

In this course we will study techniques and algorithms for creating effective visualizations based on principles and techniques from graphic design, visual art, perceptual psychology and cognitive science. The course is targeted both towards students interested in using visualization in their own work, as well as students interested in building better visualization tools and systems. The class will meet twice a week. In addition to participating in class discussions, students will have to complete several short programming and data analysis assignments as well as a final programming project. Students will be expected to write up the results of the project in the form of a conference paper submission.

There are no prerequisites for the class and the class is open to graduate students as well as advanced undergraduates. However, a basic working knowledge of, or willingness to learn, a graphics API (e.g. Javascript/D3, Python, WebGL) and applications (e.g. Excel, Matlab) will be useful. The final project can be developed using any suitable language or application. While we will cover a little bit of Javascript/D3 in class, most of the other APIs, applications and languages will not be taught in the course. However many introductory tutorials at the level required for the class are available on the web and we can help you find the relevant information as you need it. Send me (Maneesh) email if you are worried about whether you have the background for the course.

Contents

Announcements

Schedule

Week 1

W Sep 4: The Purpose of Visualization [ Readings | Submit Reading Response (by 3pm) | Slides ]

Assigned: Assignment 1 (due Sep 11 by 9am)


Week 2

M Sep 9: Data and Image Models [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Sep 11: Visualization Design [ Readings | Submit Reading Response (by 3pm) | Slides ]

Due (by 9am): Assignment 1
Assigned: Assignment 2 (due Sep 30 before class)


Week 3

M Sep 16: Exploratory Data Analysis [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Sep 18: Multidimensional Data Visualization [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 4

M Sep 23: Perception [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Sep 25: Interaction [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 5

M Sep 30: No class due to power outage

Due (please turn in by end of day on 10/1): Assignment 2
Assigned: Assignment 3 (due Oct 16 before class)

W Oct 2: Interaction II [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 6

M Oct 7: Introduction to D3 (guest lecture by Scott Murray) [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Oct 9: Wrangling Data (guest lecture by Sean Kandel) [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 7

M Oct 14: Color [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Oct 16: Using Space Effectively: 2D [ Readings | Submit Reading Response (by 3pm) | Slides ]

Due: Assignment 3
Assigned: Final Project (project proposal due Oct 28 before class)


Week 8

M Oct 21: Spatial Layout [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Oct 23: Identifying Design Principles [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 9

M Oct 28: Collaborative Visual Analysis [ Readings | Submit Reading Response (by 3pm) | Slides ]

Due: Final Project (project proposal)

W Oct 30: Crowdsourcing Visual Analysis [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 10

M Nov 4: Graph Layout [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Nov 6: Text Visualization [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 11

M Nov 11: Veteran's Day Holiday

W Nov 13: In Class Project Presentations


Week 12

M Nov 18: In Class Project Presentations

W Nov 20: In Class Project Presentations


Week 13

M Nov 25: Conveying Shape: Lines [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Nov 27: No class


Week 14

M Dec 2: Conveying Shape: Shading [ Readings | Submit Reading Response (by 3pm) | Slides ]

W Dec 4: Animation [ Readings | Submit Reading Response (by 3pm) | Slides ]


Week 15

F Dec 13: Final Poster Session - 1-3pm, 5th Floor Soda Hall, Open to the Public


Information

Course Numbers: CS294-10 Visualization
Units: 1 or 3
Instructor: Maneesh Agrawala (maneesh at cs.berkeley.edu)
Meeting: 306 Soda Hall, MW 5:30-7pm

Office Hours:

Textbooks:

Your best bet is to order them online.
Please order soon. Readings will be assigned in the first week of class.

Requirements

Class participation (10%)

Assignment 1: Visualization Design (10%)

Assignment 2: Exploratory Data Analysis (15%)

Assignment 3: Creating Interactive Visualization Software (25%)

Final Project (40%)


Late Policy: For assignments we will deduct 10% for each day (including weekends) the assignment is late.

Plagiarism Policy: Assignments should consist primarily of your original work, building off of others' work--including 3rd party libraries, public source code examples, and design ideas--is acceptable and in most cases encouraged. However, failure to cite such sources will result in score deductions proportional to the severity of the oversight.

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Credits

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