Overview

This is the course website for HCDE/DATA 511: Information Visualization/Data Visualization and Exploratory Analytics.

Recent advances in computation, data management, and sensors are leading our society to generate an ever-increasing flood of digital information. Submerged within the data deluge lies a wealth of information that is potentially valuable to businesses, governments, scientists, and all human communities. In order for data to be of use to humans, we need to understand how to explore and communicate this information effectively so that humans can make sense of and draw valuable insights from the data around us. The visual system is the highest bandwidth channel into the human brain.

The goal of data visualization is the unveiling of the underlying structure of large or abstract data sets using visual representations that utilize the powerful processing capabilities of the human visual perceptual system.

Instructor

Cecilia Aragon
407A Sieg Hall
Office Hours: Thursdays 4-5pm in 407A Sieg
Email: aragon (at) uw. edu

TA

Taylor Scott
424 Sieg Hall
Office Hours: By appointment
Email: omni (at) uw. edu

Course Summary

This course covers the key design principles and techniques used in visualizing, exploring, and analyzing very large data sets, together with the perceptual principles that support them. It is structured to provide both concrete experience with real data and tools as well as a broad overview of the rich world of data visualization. Students will learn both how to design and how to explore, analyze, implement, and evaluate.

The following topics will be included: The design and presentation of digital information. Use of graphics, animation, visualization software, and hypermedia in presenting and analyzing large and complex data. Vision and perception. Methods of presenting vast and complex data sets to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces.

There are many related topics that this class will not address. These include: computer graphics and visualization as an artistic enterprise.

Students will be required to do reading assignments, perform in-class exercises in design and analysis, participate in online and in-class discussions, and complete several visualization assignments and a group project that will consist either of creating or enhancing a visualization system or technique. Projects will be interdisciplinary in nature and in most cases will involve programming, visualization design, and user interface design. Students will be expected to write up the results of the project in the form of a research paper. There will be no final exam.

This course is based on many prior courses in visualization, including material from UC Berkeley professors Marti Hearst and Maneesh Agrawala, UW CSE professor Jeffrey Heer, UW HCDE instructor Polle Zellweger, and many others. We would like to gratefully acknowledge the generosity of these professors and other experts in sharing teaching materials. All material is used with permission.

Student Learning Goals

By the end of this course, students will be able to:

• Understand the basic data types and effective visual mappings
• Describe the key design guidelines and techniques used for the visual display of information, including their relationship to human perception
• Apply fundamental data visualization techniques and theoretical principles to real-world problems
• Critically analyze the design and presentation of digital information
• Design static and interactive visualizations to effectively present information to users and/or to enable data exploration, using real data and a human-centered process
• Incorporate visualization techniques into human-computer interfaces

Class Meetings

Class meets Thurs 6:00pm-9:50pm in 233 Sieg Hall, the Design Lab on the second floor. The format of the class will be a mix of lecture, discussion, analyzing visualizations, in-class activities, and design studio.

Grading

Grades will be determined as follows:

• 10% in-class work
• 20% readings and class participation
• 30% assignments
• 40% final project

Late assignments will not be accepted after the first week of class. In-class work and class participation cannot be made up. If you miss a class, you will receive a zero for the work done in class that day. Please do not ask the professor or TA what you missed during class; check the website or ask a classmate. Required posts to the class discussion board must be made before the due date or you will receive a zero for that work.

Final projects cannot be turned in late.

Readings and Books

Readings will consist of one required text: Stephen Few's Now You See It, and a number of papers that will be accessible online or handed out in class.

Highly recommended but not required:

• Edward Tufte's The Visual Display of Quantitative Information, 2nd ed., 2001.
• Colin Ware's Information Visualization: Perception for Design, 3rd ed., 2012.

Guide to using the Tableau software package:
The Beginner's Guide to Data Visualization.

Software

We'll be using the Tableau software package. It works under Windows and Mac. You will receive a code for accessing it; do not share this with others. All students receive free access to Tableau's data visualization software through the Tableau for Teaching program.

You may also use the free Tableau Public software package.

Optionally, you may also be working with R or d3, a free JavaScript library for manipulating documents based on data, or other visualization tools or programming languages. See the resources page for further tools.

Policies

The following general policies apply to this course:

• Respect: If there were only one policy allowed in a course syllabus, I would choose the word respect to represent our goals for a healthy and engaging educational environment. Treating each other respectfully, in the broadest sense and in all ways, is a necessary and probably sufficient condition for a successful experience together.
• Attendance: Students are expected to attend class regularly.
• Late Assignments: Late assignments will not be accepted. If your assignment is late, you will receive a zero score.
• Participation: Active participation in class activities is one of the requirements of the course. You are expected to engage in group activities, class discussions, interactions with your peers, and constructive critiques as part of the course work. This will help you hone your communication and other professional skills.
• Collaboration: Working in groups or on teams is an essential part of all design and engineering disciplines. As part of this course, you will be asked to provide feedback of your peers' work.
• Academic Integrity: Simply stated, academic integrity means that you are to do your own work in all of your classes, unless collaboration is part of an assignment as defined in the course. In any case, you must be responsible for citing and acknowledging outside sources of ideas in work you submit. Please be aware of the HCDE Department's and the UW's policies on this: HCDE Academic Conduct. These will be strictly enforced.
• Assignment Quality: You are expected to produce work in all of the assignments that reflects the highest standards of professionalism. For written documents, this means proper spelling, grammar, and formatting. For visually-oriented material, I recognize that not everyone is an accomplished graphic designer, but you should strive for neat and clear visual communications in your work.
• Privacy: Students have the right for aspects of their personal life that they do not wish to share with others to remain private. Please respect that policy.
• Accommodations: To request academic accommodations due to a disability, please contact Disabled Student Services: 448 Schmitz, 206-543-8924 (V/TTY). If you have a letter from DSS indicating that you have a disability which requires academic accommodations, please present the letter to me so you can discuss the accommodations you might need in the class.
• Permissions: Unless you notify me otherwise, I will assume you will allow me to use samples from your work in this course in future instructional settings.
• Disclaimer: This syllabus and all associated assignments, requirements, deadlines and procedures are subject to change.

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