Course Details
Catalog Description
This is a foundational course on information design and aesthetics, promoting data literacy and visualization competencies for designers and analysts. With a focus on social engagement, this course prepares students with the critical skills to advocate visually and the intellectual context to engage in a world in which data increasingly shapes opinion, policy, and decision making. Students will learn to curate and uncover insights from large and complex data sets using code-based visualization platforms, digital design software, or analog prototyping techniques to create plots, graphs, indexes, and maps that explore the database as a cultural form.
Students will study the fundamentals of design and the grammar of graphics while investigating hierarchies, patterns, and relationships in data structures. Students will examine the role of scale, proportion, color, form, structure, motion, and composition in data visualization. The intent of this course is to build a community among the students and the larger discipline.
Students will familiarize themselves with the necessary vocabulary to communicate and collaborate with data visualization professionals in future contexts. A series of presentations, screenings, readings, and discussions expose students to artists and designers working in the context of data visualization and the digital arts. Each student will select a research topic and present a research report in conjunction with an in-class discussion. Assignments are invitations to invent and experiment.
Prerequisite: Graduate Comm. Design student standing
Format: 3 credit studio
Course Goals
As part of this course, you will:
- Develop a deep understanding of the various methods and techniques of modern data visualization as well as its historical context.
- Develop skills to design effective visual communication and information displays by learning a framework for critical exploration and invention.
- Gain experience in describing, analyzing, and evaluating various data visualization approaches through presentations and critiques.
- Give students an understanding of the process of acquiring, analyzing, refactoring, and visualizing data.
- Introduce the building blocks of visual data representation (bar charts, scatter plots, network diagrams, etc.), know when each is appropriate, and learn to avoid their associated pitfalls.
- Process and analyze a variety of data types: quantitative, qualitative, text, and geospatial.
Learning Outcomes
Through projects and in-class exercises, you will:
- Understand the fundamentals of design and the grammar of graphics as they are applied to hierarchies, patterns, and relationships in data structures.
- Recognize the role of scale, proportion, color, form, structure, motion, and composition in data visualization.
- Be able to design effective visual communication and information displays by learning a framework for educated exploration and invention.
- Be able to establish Hypothesis Testing as a working method for developing visual explanations and discovering the ‘story’ within a dataset