This repository contains my assignments for the Major Studio 1 course at Parsons School of Design's MS in Data Visualization.
In an attempt to illustrate the urgent need to provide adequate mental health aid and more humane conditions inside prison, I used data from the UN's Office on Drugs and Crime and from the Institute for Health Metrics and Evaluation, Global Burden of Disease, to compare deaths by suicide inside and outside prison facilities in 2019.
This segment of the course examines the fundamentals of quantitative data. Students will gain an understanding of how data is gathered, the databases and other formats by which it can be stored, the APIs by which it can be accessed, and how it may need to be “cleaned” before use. Design exercises will use web-based libraries (such as D3, R or Processing) to create visualizations of sample data sets. Through the exercise, students will learn how to determine meaningful patterns along with best practices for visualizing them. Students will be given a data set to design static visualizations for an intended audience. Through the exercise, students will explore the most effective way to communicate the information. Group discussion and critique of the work will highlight best practices.
The assignment repository can be found here.
The second segment of the course will introduce the concept of qualitative data and how it can be represented. Students will explore manually-created design alternatives to sample data sets and examine how those solutions effectively communicate the content, as well as present a narrative context for the recipient. Students will be given a data set and will design a static visualization of the content for a proposed intended audience. Through the exercise, students will explore the most effective way to communicate the information. Group discussion and critique of the work will examine best practices.
The assignmnent repository can be found here.
This segment of the course will introduce the design elements of dynamics and interactivity. Students will gain an understanding of how these elements can be used to further communicate meaning within data sets. Design exercises will introduce additional web-based tools to incorporate dynamics and interactivity into new design explorations. Special emphasis will be placed on the narrative that is generated by the user’s active exploration of the data, how their understanding of the data is enhanced, and how the designer can effectively guide that journey. At the instructor’s discretion, students may explore how crowdsourcing can be used to generate or filter the data. Students will choose a data set in coordination with the instructor and design a dynamic or interactive visualization of the content for an intended audience. Through the exercise, students will explore the most effective way to animate the information. Group discussion and critique of the design solutions will highlight best practices.