AIGA Design Census


AIGA Census (
by Sara Fields, Treat Swarstad, Bettina Chou, Emily Mongilio, and Lily Fulop

Eyes on Designers
by Christine Chen, Mauro Magarelli, Zoe Attwood, and Ikjong Choi

AIGA Design Census (
by Alice Fang, Rachel Lee, and Jaclyn Saik

AIGA Monsters (
by Maddy Cha, Alissa Chan, Katie Chen, and Rachel Glasser

Glimpse Into the Future (
by Mimi Jiao, Jenna Kim, Sophia Kim, and Jenni Lee

Duration: 6 weeks
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Bookmark Project

Project Brief

What is the current state of design, and where is its future headed? Since 2017, AIGA and Google have published yearly surveys called ‘Design Census’ (, which surveys the design field on subjects such as salary, satisfaction, skills and stability. It provides a multifaceted view of designers working in various design environments and the opportunity to interpret and curate its data. In groups of three or four, you will use the latest ‘Design Census’ to create data-driven artifacts and/or systems that yield various interactive communication artifacts.

Learning Objectives

  • Comprehend your role as a designer working with data to determine the priorities in design decision making.
  • Examine the relationships across data to construct meaningful patterns. 
  • Apply principles of graphic design and typography to create compelling representations of data.
  • Explore relationships between visual elements and meanings to effectively communicate your message/story 
  • Build visual systems to provide consistent experience to your audience across various media. 
  • Utilize time and interactivity to design dynamic media that can maximize audience engagement.


  • High-fidelity final outcome based on the media of your choice. You are encouraged to utilize both print and digital media.
  • A Medium post including all your processes. In addition to the final outcome, your work will be evaluated based on the breadth and depth of processes.


  • Bertin, Jacques, and William J. Berg. Semiology of Graphics: Diagrams, networks, maps. Redlands, CA: ESRI Press, 2010. Print.
  • Freyer, Conny, Sebastien Noel, and Eva Rucki. Digital by Design: Crafting technology for products and environments. Thames & Hudson, 2011. Print.
  • Fry, Ben. Visualizing Data: Exploring and Explaining Data with the Processing Environment. Sebastopol: O'Reilly Media, Inc. 2007. Print.
  • Klanten, Robert. Data Flow: Visualizing information in graphic design. Berlin: Gestalten, 2008. Print.
  • Klanten, Robert and Ehmann, Sven. Data Flow 2: Visualizing Information in Graphic Design. Berlin: Gestalten, 2010. Print.
  • Maurer, Luna, Edo Paulus, Jonathan Puckey, and Roel Wouters. Conditional Design Workbook. Amsterdam: Valiz, 2013. Print.
  • Richardson, Andrew. Data-Driven Graphic Design: Creative Coding for Visual Communication. London: Fairchild books. 2016. Print.
  •  Lima, Manuel. Visual Complexity: Mapping patterns of information. New York: Princeton Architectural Press, 2011. Print.


The project has quickly become one of the most popular projects in the curriculum of our Communications track in CMU’s School of Design. The project is open-ended to encourage students to explore the state of design today by themselves through the Design Census data, as well as to use data as a medium in creating artifacts and systems for interactions. Students gain an understanding of the diverse contexts by analyzing and synthesizing data (the survey questions and responses), and identify opportunities and limitations based on the data. 

Considering the size of the dataset (i.e., 9,429 people answered 38 questions in the 2019 Design Census), some programming skills and data literacy are inevitable to work efficiently. At the same time, it requires the students to develop a high-level understanding and scope of the questions and the relations among them. The project is ideal for groups of students (3-4 per group) to develop compelling concepts that conceive stories and metaphors through the aggregation and curation of data. 

Depending on course objectives, the project brief can be framed in various ways. There has been a range of students’ outputs, categorized in the following:

  • Custom tools that enable users to explore data
  • Stories that communicate data in engaging ways 
  • Visual metaphors that humanize data
  • Systems that provide personalized experiences
  • A fuse of data that yields new content and insights


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