Press "Enter" to skip to content

[JOB / TEACHING] Instructor of Data Visualization and Information Aesthetics, Parsons School of Design

Data Visualization and Information Aesthetics
PGDV 5100
Wednesdays, 7-9:40pm
Credits: 3
Learning Envelope: Contact 3 / Task 6 / Total hours 9
Open to: Graduate students across the New School
This is a seminal course on information design and aesthetics. Students will study graphical theory, graph grammar, and investigate hierarchies, patterns, and relationships in data structures. Students will examine the role of scale, proportion, color, form, structure, motion, and composition in data visualization. Using computational methods, students will create drawings, graphs, indexes, and maps that explore the database as cultural form. The function of this course is to build a community among the students and orient them to the whole program.
This studio course is an introduction to data visualization, promoting data literacy and visualization competencies for visual artists, 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 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 cloud-based web technologies, JavaScript, and Processing, students will create drawings, graphs, indexes, and maps. Software influences all aspects of visual media. Media theorist Friedrich Kittler argued that students today should know at least two software languages, “only then they’ll be able to say something about what ‘culture’ is at the moment” (Manovich, 2013). The class will draw upon programming skills acquired in other classes. Basic coding and design knowledge are expected.
Students will familiarize themselves with the necessary vocabulary to communicate and collaborate with data visualization professionals in future contexts. Throughout the course, students work with Canvas to collect and share resources and submit assignments. A series of presentations, screenings, readings, and discussions exposes 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. Creative and ambitious experiments are evaluated high, while obvious and easily attained solutions are evaluated low. The complexity of the assignments increases as the semester progresses. Students are required to document their iterative design process and have it available to present during each class session. Active contribution during class is required. All assignments must be completed to pass the course. Assignments are only considered complete when available on Canvas. Late assignments and attendance will reduce grades proportionally.
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 educated exploration and invention.
Gain experience in describing, analyzing, and evaluating various data visualization approaches through recurrent presentations and critiques.
Develop Exercise 1: Visualize time (week 3)
Develop Exercise 2: Visualize  quantities, categories, and summarized data (week 5)
Develop Exercise 3: Visualize textual and qualitative data (week 7)
Develop Exercise 4: Visualize geospatial data (week 9)
Present a research report on subject assigned during first class session (due on individually assigned date)
Document research and design process in the Learning Portfolio (due weekly)
Collect sources for the final project (due: week 10)
Develop a proposal for the final project (due: week 11)
Create a prototype for the final project (due: week 13)
Create and Demonstrate the final project (due: week 15)