Wednesday, September 16, 2015

HCDE 411 - Information Visualization open to non-majors

Students don’t need to have taken the prerequisites, but they should have coursework or equivalent experience in programming OR visual design. Anyone interested in data science should find this class particularly useful since the focus will be on visualization of large data sets. The course will be project-based, so students can focus on their own research projects.

HCDE 411 - Information Visualization
Autumn 2015
MW 11:30-1:20
Prof. Cecilia Aragon
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 information visualization is the unveiling of the underlying structure of large data sets using visual representations that utilize the powerful processing capabilities of the human visual perceptual system.
This course covers the key design principles and techniques used in visualizing information, 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 information 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 information to the user. Vision and perception. Methods of presenting complex information to enhance comprehension and analysis. Scientific visualization. Visual analytics. Incorporation of visualization techniques into human-computer interfaces.
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 over a large data set of the students' choice. 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 final paper. Advanced students may conduct original research or focus on data visualization in any scientific, business, or other domain with the instructor's permission. There will be no final exam.
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
Interested students should contact Alex Llapitan, for an add code.