Overview

Background

Amidst the information flood in which we are currently immersed, visualizations can be a well-placed treetop. The rise of big data has the potential to inform decisions, and visual representations can play a crucial intermediate role in our daily information consumption. This course is designed to the interdisciplinary and emerging field of data science. It will cover techniques and algorithms for creating effective visualizations based on principles from graphic design, visual art, perceptual psychology, and cognitive science to enhance the understanding of complex data.

Objective 

This course particularly pays attention to the applied techniques to data visualization narratives and also takes an interest in data visualization challenges. We will draw on case studies from current hot topics, news media to visualization research. In addition to participating in class discussions, students will have to complete several scripting, data analysis and visualization design assignments as well as a final project. Students will be expected to write up the results of the project in the form of a conference paper submission.

Evaluation

Participation: 15%; Assignments: 45%; Final Project 40%

  • Students will be expected to active participate in class, including class discussion, paper summaries, show & tell through course blogs and tumblr.
  • Students will also be tasked to complete 4 assignments in two categories visualization designs and analyses, from data viz theoretical background, technology and actual implementation. Each assignment should be an individual effort.
  • Final project will be highly encouraged to incorporate each individual’s thesis. However, if you do not have a specific topic for program thesis yet, you are also encouraged to form a group of 2-3, submit a final project proposal before the first assignment due. The project will be expected to demonstrate in class / online and through out a poster session. A written final project report must follow ACM SIG double columns format. The results will be highly encouraged to submit to relevant conferences.

Textbook

The Visual Display of Quantitative Information http://amzn.to/WrywQs

Data Visualization Book Network GraphTextbook

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