Visualization and Design: Fundamentals

• CUNY Graduate Center | 5417
• 6:30 to 8:30pm | Mondays
• Michelle McSweeney (mmcsweeney@gc.cuny.edu)
• Office Hours By Appointment
• https://introductiondatavizfa21.commons.gc.cuny.edu

 ⇒⇒⇒⇒⇒ SYLLABUS ⇐⇐⇐⇐⇐⇐

Description

We live in a data-driven society where decisions are made based on analysis of “the data.” Frequently, that data is presented in the form of visualizations. The practice of visualization is one of data analysis, and it takes a deep understanding of a dataset to be able to present it visually and accurately represent the nature and nuance of the data while still telling a story or making a claim. This course situates the practice of data visualization within a larger context of data literacy and data ethics. Using Tableau Software, we will build a series of interactive visualizations that combine data and logic with storytelling and design. We will dive into cleaning and structuring unruly data sets, identifying which chart types work best for different types of data, and unpacking the tactics behind effective visual communication. With an eye towards critical evaluation of both data and method, projects and discussions will be geared towards humanities and social science research. Regardless of your academic concentration, you will walk away from this class with a portfolio of dynamic dashboards and a new interdisciplinary skill set ready to leverage in your academic and professional work.

Objectives

By the end of this class, you will be able to:

• Build interactive data visualization dashboards that answer a clear and purposeful research question
• Choose which chart type works best for different types of data
• Iterate with fluidity in Tableau Software leveraging visualization, aesthetic, and user interface best practices
• Evaluate a dataset with an eye towards bias and accountability.
• Structure thoughtful critiques and communicate technical questions and solutions
• Leverage collaborative tools, including Tableau Public, CUNY Academic Commons, and repositories of public data sets
• Contribute to the broader conversation about digital practices in academic research
• Critically read a wide range of chart types with an eye for accuracy, audience, and effectiveness
• Identify potential weaknesses in the collection methods and structure of underlying data sets
• Locate the original source of a visualization and its data

Format

This course is a hybrid lecture-studio format. The lecture will focus on the theory of data and the relationship between data, visualization, and storytelling. The studio aspect is the combination of the Tableau labs and the pin ups.

The Tableau tutorials are only available online (as both videos and pdfs) because I believe asynchronous formats are the best way to learn to use a new tool. They can be completed in any order, though they do correspond to the weekly sessions. The due dates are in the syllabus, but I will only check for completion near the end of the semester. You will not receive feedback on the labs because ultimately your lab will look a lot like the examples.

Weeks are divided into project weeks and non-project weeks. Non-project weeks follow a traditional seminar format: there will be a lecture and forum that you will need to post to. Project weeks will consist of either a meeting or a pin-up (see the syllabus for more details).

There are 3 projects. Before each project, you will submit a project proposal. The project proposal consists of 1 paragraph describing your question, the data you plan to use (specifying the variables), and a sketch of your visualization. We will have a 5-10 minute meeting to discuss your proposal. You will then complete your project.

After you complete your project, you will participate in a pin-up. This is an opportunity to get feedback from the class. The purpose of the pinups is to both practice giving and receiving feedback and it is an opportunity to envision how you can develop your project.

By the end of this course, you will have developed a deep understanding of the context around data visualization and how to effectively and ethically engage in visual communication.

***Fall 2021 ADDENDUM***

This course is intended to be taken mostly in person. The format of each session is indicated in the syllabus. All students will complete all labs online and will participate in two 10 minute 1:1 meetings online. Lectures and pin ups will be held in person and we will follow the GC mask and social distance guidelines. If you are not comfortable coming to campus for any reason, you may watch the pre-recorded lecture in lieu of attending in-person. If you will miss the pin up for any reason, you must make alternative arrangements.

Assignments

During this course, you will complete four graded assignments: 3 projects and a white paper. You will get feedback on these 4 items. You will likely turn in each project before you feel fully ready to do so, and will have the opportunity to submit revisions until you’re satisfied with the outcome. 

 You will also complete tutorials on Tableau, forum discussions, and critiques, these are graded on completion and you will not receive feedback on them. 

Submit your PROPOSALS & White Paper via email to mmcsweeney@gc.cuny.edu. 

Post the link to your PROJECTS (the CUNY Academic Commons Page with your project and text) to the respective spreadsheet.

Post your Tableau Tutorials/Labs to your Tableau Public Site. 

Post the Forum responses and Critiques to the Group Forum.

Project 1

15% Final Grade | Guidelines
Visualizations built with New York City’s 311 data

Project 2

20% Final Grade | Guidelines
Visualizations of a data set you’ve created

Final Project (Project 3)

25% Final Project| Guidelines
Visualizations answering an independent research question using a data set of your choice

White Paper

10% Final Grade | Guidelines
A 1,500-4,000 word final reflection on data, visualization, and iteration

Critiques

15% Final Grade | Critiques Guidelines

Tableau Labs

15% Final Grade | Completion of Tableau Labs

 

Schedule

There are 5 SYNCHRONOUS classes via ZOOM 

8/30 6:30-8:30pm (ET)

10/4 6:30-8:30pm (ET)

11/1 6:30-8:30pm (ET)

12/6 6:30-8:30pm (ET)

12/13 6:30-8:30pm (ET)

 

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