CS 7250 –Information Visualization: Theory and Applications

Covers foundational as well as contemporary topics of interest in data visualization to enable the effective representation of data across disciplines, including examples drawn from computer science, physical sciences, biomedical sciences, humanities, and economics. Topics include data visualization theory and methodology, visualization design and evaluation, visual perception and cognition, interaction principles, and data encoding and representation techniques. Students who do not meet course restrictions may seek permission of instructor. (from the course catalog)

Cutting-edge data visualization with web technologies

This version of the course introduces advanced web technologies for visualizing and communicating insights with data. Students will learn to create custom interactive visualizations. Classes will explore a series of case studies ranging from data journalism to data science. With a combination of in-class exercises and outside assignments, students will gain experience with the basics of user-interface design (interactive elements such as sliders, brushes, buttons, etc.) and interactive exploratory data analysis with cartography, animation, 3-D graphics, and dashboards.

This course uses Observable notebooks for event-driven, reactive and interactive visualizations. These notebooks provide a flexible medium for protoyping ideas and developing applications with powerful open source libraries. Students will use them to gain experience with the best practices and techniques of collaborative coding (e.g., forking, importing, recommending, version control). Project-based learning will also allow students to gain experience working in a team. The same technologies can be used to create fast, beautiful data apps, dashboards, and reports. Students can use whatever language they like for data prep (e.g., Python, R, SQL, or anything else). The term project will provide students an opportunity to explore their passions and to start or advance their own portfolio website(s).

Some representative case studies:

• America’s Cup (New York Times) – time-series animation for sailboat-racing fans
• Tensorflow playground – neural network in a browser
• Remarkable cartography – built with D3’s geospatial capabilities
• Brushable earthquakes – interactive visualizations for exploratory data analysis
• Liquid Fun – fluid physics simulation in a browser
• MapLibre & deck.gl – 3-D, open source mapping libraries for data visualization

Learning outcomes

Students will learn innovative data visualization skills that can be applied in a wide range of application areas. These skills bridge the gap between data science and web development. By the end of the course, students will be able to…

• Create interactive visualizations with modern web technologies.
• Tell a story with data and animate an algorithm.
• Create dashboards with a variety of chart types using open source software libraries.
• Perform browser-based data exploration in a collaborative development environment.
• Develop browser-based geospatial mapping applications.
• Apply cutting-edge 2-D and 3-D libraries such as D3, Observable Plot, Three.js, MapLibre, Deck.gl.
• Deploy and maintain a website that can be part of their own data-driven project portfolio.
• Gain insights on the business models for proprietary platforms such as Mapbox, Google, Tableau, etc.

Approach

• Classes
  • The majority of the class time will involve hands-on exercises with live coding.
  • For the most part, outside reading and videos will take the place of in-class lectures.
• Assignments
  • Reading, videos and homework assignments will expose students to ideas and technologies.
  • Observable notebooks will be used for both individual and team-based learning.
• Participation
  • Students are expected to participate in class, through assignments and self-motivated exploration.
  • Students should have a github account, which they’ll use to authenticate at observablehq.com.
• Term project
  • Term projects comprise an important part of the course and will dominate the second half of the semester.
  • Students may select from project options presented in class or they may choose their own path.

Prerequisites

There are no formal requirements. Previous familiarity with web technologies will be helpful but is not required. The course uses JavaScript, which is the rapidly evolving language that’s built into all modern browsers. While no previous experience with JavaScript is necessary, students should be proficient with object-oriented programming in at least one modern language such as Python or C++. Relevant web technologies (HTML, CSS, etc.) will be introduced as needed.