Data Visualization – Introduction to the data pipeline with a focus on visualization

Queens College
DESN 270
Data Visualization

Spring 2024
Wednesdays, 1:40 PM – 5:30 PM
Online and Queens College Makerspace
Slack Channel
Class one-on-ones 3:30PM – 5:30PM: Calendly

No Class
February 28 (Classes follow Monday schedule)
April 24 (Spring Recess)

Coding Examples

YouTube Channel

Course Description

The massive amounts of data that we produce as a culture is steadily rising year after year. This ever-growing sea of information needs to be understood. Since we are all naturally visual people, the best way to understand this data is to graphically interpret it as data visualizations.

Over the course of this semester we will cover this entire process. First sourcing publicly available data sets. Then analyzing these data sets to pull out the points of interest. And finally designing visualizations based on our findings for a specific audience. The first portion of the semester will be focused on printed infographics and the second half will focus on both interactive interpretations of the data using HTML5 as well as data sculpture using digital fabrication tools like 3D printing, laser cutting and CNC routing.

Course Objectives

First Half of the Semester
- Collect your own personal data throughout the semester using the Gyroscope App.
- Research a cause, non-profit, or subject you are passionate about.
- Source at least two separate datasets about that the selected topic.
- Clean the datasets and pull out the points of interest.
- Write a creative brief defining your audience, findings and what you hope to achieve.
- Visualize your findings as a 20″ x 30″ poster and share it as a PDF in our class Slack channel for midterm presentations on Zoom.

Second Half of the Semester (OPTION 1)
- Understand the basics of HTML5 (HTML, CSS and JavaScript).
- Using HTML5 along with the libraries and software we discuss, create a one page website using live data using an API (application programming interface), your personal data you have collected OR recreate your midterm as an interactive website.
- Present your website and findings to the class for your final project on Zoom and Slack.

Second Half of the Semester (OPTION 2)
- Learn the basics of digital fabrication (3D Printing, CNC Routing, Laser Cutting).
- Using data that you either have collected or found create a physical data sculpture or interface based on the values in the data.
- Present your physical sculpture or interface as well as your findings to the class for your final project on Zoom and Slack.

Learning Outcomes
This course allows students to explore the world of data. They will become very comfortable with the entire data pipeline from finding and sourcing data, cleaning dirty data, doing basic data analysis, visualizing data for understanding and visualizing data for presentation. The main tools used in this course include Microsoft Excel, Google Sheets, Adobe Illustrator and Datavisual.

The second half of the semester students will be given the option to go down the web path or the physical path. The web path will look at how to work with data and the web and will be covering some basic programming languages like HTML, CSS and JavaScript. We will also be covering how to get live data from APIs (Application Programming Interfaces) to be displayed on your own websites. The physical path will look at how to use digital fabrication tools like 3D printing, laser cutting and CNC milling to create data driven sculptures and physical installations.

Course Requirements
Class participation is mandatory. You are expected to be present, to participate in a positive, constructive manner, and to produce work that is full of energy, completed and presented to the best of your ability.

It is your responsibility to turn in work on time, to make up any missed assignments, and to catch up with the class in the event of an absence. Late work is unacceptable; however, this work can be turned in for partial credit. If you know you are going to be absent, contact the professor by email in advance. For the most up-to-date information (including what is due next class) visit the class website: dataviz.danne.design.

This is a hands-on course and regular attendance is necessary for participation. You will be graded on in-class participation. If you know you are going to be absent, contact the professor by email in advance. Students who miss numerous classes will find it difficult to pass the course. Visual assignments and projects will be graded based on: one for technical merit, concept and your demonstrated ability to understand the code. Your final grades will be calculated by the following: 80% project, 20% participation. You are expected to spend as much time working outside the classroom as you work inside the classroom. Schedule your time accordingly.

Textbook
The Functional Art, by Alberto Cairo

Professors Contact Info
Name: Danne Woo
Email: [email protected]
URL: dannewoo.com
Office Hours: calendly.com/dannewoo/office-hours
Medium Articles: dannewoo.medium.com
Personal Data Visualization Projects: Instagram and Twitter

Grading
Attendance:
Two (unexcused) absences result in grade drop and four absences result in a failing grade. Late or early departure from class (15 minutes) is the equivalent of ½ absence.

To earn an A:
All class work and homework is excellent. Projects have been completed when assigned. The work shows a development and understanding of the principles discussed in class. It is presented immaculately. There is regular and prompt attendance and participation during critiques and an enthusiasm toward the material being presented throughout the semester. This is exceptional work.

To earn a B:
All assigned work completed in a thorough manner. An understanding of the principles and lessons covered in class is evident. The student comes to class regularly and on time and participates in critiques and discussions. This is better than average work.

To earn a C:
Most class assignments and homework have been completed. Regular attendance but minimal or negative class participation. There is understanding of most of what’s being presented in class. This student shows some interest in the course content. This is average work.

To earn a D:
Most class assignments and homework have not been completed. Marginal effort made to understand the course objectives and very little or negative participation on behalf of the student. Spotty attendance. This means below average work.

To earn an F:
Student has not completed 1⁄3 of the course work and has missed too many classes. This student doesn’t participate or has a bad attitude and shows no interest. It means not enough work, attendance, and/or effort to pass the class.