"90% of the data in the world today has been created in the last two years." – IBM report on big data
"Getting information from a table is like extracting sunlight from a cucumber." – Arthur and Henry Farquhar
⬇️ Jump right to the Course Calendar ⬇️
| Instructor | Prof. Jeff Thompson (please call me Jeff) |
|---|---|
| jeff.thompson@stevens.edu | |
| Meeting times | Thursdays, 9am–12.50pm, Morton 201 |
| Student hours | Tuesdays, 2–3pm (Morton 208) and by appointment (Zoom) |
What does a day of flight paths in the US look like? What can we learn about NYC by mapping shadows? How can a Twitter bot help us experience the minute details found in census data? Data visualization is a complex and varied field, found in many disciplines where the methodology ranges from scientific (full of stats and academic papers) to interactive online projects for governments and non-profits to illustrated infographics found in newspapers and even fine art that uses data as an input. This semester, we will explore the many ways that design and data can intersect. Through a series of creative research projects, we'll think about the design challenges that data presents, how to tell stories with data, and how we record and represent the world through data.
We'll begin by considering a broad idea of what data might be and different ways of recording and presenting it. We'll explore really huge numbers and creative ways to show them. After that we'll use a range of tools, from Adobe Illustrator to Excel to code, letting us create visualizations in a range of formats. These projects will involve lots of research, finding our own data, and will be framed around pressing contemporary issues. The last third of the semester will be spent on a large-scale, open-ended visualization project of your choosing. Along the way, we'll also take a look at lots of visualizations made over the last thousand+ years; look at ways to clean, parse, and publish our own datasets; and see the varied career paths that designers interested in data can take.
This class assumes you’ve never worked with data before but does assume you've written at least a little code; if you've done lots of this before, you should leverage that experience to push your work and make more complex projects. You're also encouraged to combine what we do with any additional software, materials, and processes that you're familiar with and/or excited about.
See the syllabus for course format, policies, grading, etc.
Please note this is subject to change – be sure to check Canvas, this page, and your email regularly.
- Jan 20: Visual Evidence
- Jan 27: Representing Numbers
- Feb 3: One/Million/Billion Dollars
- Feb 10: Time Series (Climate Change 1)
- Feb 17: Time Series (Climate Change 2)
- Feb 24: Time Series (Climate Change 3)
- Mar 3: Infographics (Race in America 1)
- Mar 10: Infographics (Race in America 2)
- Mar 17: Spring break, no class!
- Mar 24: Infographics (Race in America 3)
- Mar 31: Infographics (Race in America 4)
- Apr 7: Infographics (Race in America 5) / Final Project 1
- Apr 14: Final Project 2
- Apr 21: Final Project 3
- Apr 28: Final Project 4
- Exam period (May 11, 9–11am): Final crit