MIT 4.032 / 4.033
Information Design + Visualization
7 February – 10 May 2024
Instructor
Ben Fry – fry at mit dot edu
Teaching Assistant
Jin Gao – gaojin at mit dot edu
This course is an introduction to working with data for exploration and explanation. The course mixes history and theory of information with a series of projects that apply the ideas directly. Students will start with basic data analysis, then learn about visual design and presentation, followed by more sophisticated interaction techniques. Topics include storytelling and narrative, choosing representations, understanding audiences, and the role of practitioners creating tools to help people work with and make sense of information. Experience with code and/or design may help, but it is not expected or required.
Goals
This class is not a “how to” on creating data visualizations. There are many books, frameworks, and online tutorials for recreating popular work seen online. Those resources can be very useful, but it’s something better learned on your own time. This course is focused on making sense of data, and helping others do the same. We use a mix of work from inside and outside the field, plus professional work to demonstrate different ways of looking at narrative and interactive information design as broadly as possible.
Units and Registration
Listed as 2-4-6, but 1-2-9 would be more accurate. About an hour of lecture, two hours lab, and 9 hours homework per week. Bottom line, expect 12 hours/week.
Listeners are not allowed: this is a hands-on studio course. Similarly, pass/fail is not an option.
We like to have students from as many different departments as possible. Cross-registration from other schools is also welcome.
Assignments and Grading
Because we focus on iteration, expect frequent assignments. They'll always be due 9pm the evening before class. Late assignments are not accepted for credit, except when excused in advance.
Letter grades will be assigned at both the middle and end of the semester. Only the end of semester grade is on record. The following criteria are used for assessment:
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Completion – Were the projects completed on time?
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Design – What was the quality of the concept? Has effort been made to lend a unique perspective? Was there enough design iteration and process sketching?
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Code – What is the student's understanding of code? Were they able to iterate and modify code to implement a concept as intended?
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Participation – Did the student attend class? Arrive on-time? Did they participate in class lecture discussions and provide feedback for other students during critique? (Absences must be excused in advance!)
Design + Code = 70% of grade
Completion + Participation = 30% of grade
Each of these pieces are important, and interrelated:
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Completion – This course moves quickly, so if an assignment is missed or not completed in time, it will be very difficult to catch up. Each new assignment builds upon the previous, so missed steps are not an option. This is also about being considerate to the course staff: time spent managing late projects and exceptions takes away from time dedicated to the rest of the group.
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Design – The “design” of the projects is not about what things look like. It’s about how they work and how they help the intended audience think about a set of data. The first attempt at a design will always be insufficient, and many iterations will be required as you refine your ideas. An all-nighter won’t give you enough iteration to work through the necessary steps for a project. Focus on smaller steps and getting feedback on them before doing your final push. If this is unfamiliar, it will be one of the most important things you can learn from this course.
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Code – This is not a coding class. If you know how to code, you’ll find that part of the course easier, but you’ll still need to put considerable effort into the design and conceptual part of what you create. On the other hand, if you’re not familiar with code, we’ll help you along and can assure you that you’ll be able to figure it out—but only if you attend class and are engaged.
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Participation – Significant deductions will be made for students who don't engage or participate. Laptops are essential tools in this class but should not be used during lectures. We have limited class time each week, so make use of it! Starting late or leaving early is not an option—even if it's a working session.
Approach
It is important to understand that this is different from a course in the sciences or engineering because there are fewer “correct” answers: we’re teaching you an approach and skills for thinking about data and design problems.
However, it’s also not just a loosely structured art class: there are important objective truths to learn, practice, and understand.
Schedule
There will usually be an assignment for the next class, but most are sketches or progress check-ins for a longer project. We will have three units: film (deconstruction/reconstruction), clocks & color, and weather & context. These represent three “projects” which will each have a letter grade, and then we finish out the semester with a longer final project that ties everything together.
Assignment links will be posted on the front page for the course, or the assignments page. We will adjust this schedule along the way, to account for the composition and interests of the class, and how the semester is moving.
Week 1 Introduction |
Wednesday 2/7 Lecture: Course Overview |
Thursday 2/8 |
Friday 2/9 Discussion: Two examples of information design/data visualization Lecture: deconstructing and reconstructing stories |
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Week 2 Deconstructing Narratives |
Tuesday 2/13 |
Wednesday 2/14 Discussion: movie choices, film poll, identifying threads and themes |
Thursday 2/15 |
Friday 2/16 Crit: project progress |
Week 3 Reconstructing Narratives |
Tuesday 2/20 |
Wednesday 2/21 Crit: discussing assignments Discussion: taking a step back |
Thursday 2/22 |
Friday 2/23 Crit: latest updates Brief Lecture: Swiss poster design |
Week 4 Finalizing Narratives |
Tuesday 2/27 Near-Final Draft due |
Wednesday 2/28 Crit: Latest assignments Lecture: more storytelling |
Thursday 2/29 Final Poster due |
Friday 3/1 Crit: Final posters |
Week 5 Code and Iteration |
Tuesday 3/5 |
Wednesday 3/6 Lab: Sketching and coding with clocks |
Thursday 3/7 Clock Variations due (extended to Friday morning) |
Friday 3/8 Crit: Clocks |
Week 6 Color and Context |
Tuesday 3/12 Clock Iterations due |
Wednesday 3/13 Crit: Clock Iterations Guest Lecture: Color |
Thursday 3/14 Color Clocks due |
Friday 3/15 Crit: Color clocks |
Week 7 Data in Context |
Tuesday 3/19 |
Wednesday 3/20 Lab: Context clocks |
Thursday 3/21 |
Friday 3/22 Lab: Finishing clocks |
Spring Break | ||||
Week 8 Final Project kickoff |
Tuesday 4/2 |
Wednesday 4/3 Guest Lecture: “Scaled in Miles” (Mark Schifferli) Discussion: Project Ideas |
Thursday 4/4 |
Friday 4/5 Crit: Refining Project Ideas |
Week 9 Final Project: Finding and Analyzing Data |
Tuesday 4/9
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Wednesday 4/10 Guest Lecture: Olivia Glennon Lab: No Ceilings data |
Thursday 4/11 Data Sets due |
Friday 4/12 Lab: Analyzing Found Data Lecture: Final Project |
Week 10 Final Project: Reading & Representing |
Tuesday 4/16 |
Wednesday 4/17 Lab: Reading and Parsing Data |
Thursday 4/18 |
Friday 4/19 Lecture: Perception & Representation |
Week 11 Final Project: Design and Development |
Tuesday 4/23 Visual Draft due |
Wednesday 4/24 Crit: Representation Progress |
Thursday 4/25 Second Draft due |
Friday 4/26 Discussion: Project Feedback |
Week 12 Final Project: Refinement and Testing |
Tuesday 4/30 Functional Draft due |
Wednesday 5/1 Discussion: Project Feedback |
Thursday 5/2 |
Friday 5/3 Discussion: Project Feedback |
Week 13 Final Project: Refine, Document, and Present |
Tuesday 5/7 |
Wednesday 5/8 Last Crit, Last Lecture |
Thursday 5/9 |
Friday 5/10 Final Presentations |