Data Visualization for Architecture, Urbanism and the Humanities

Visual Studies A4892 · Spring 2018

This course provides an introduction to data visualization theory and methods for students entirely new to the fields of computation and information design. Through a series of in-class exercises and take-home assignments, students will learn how to critically engage and produce interactive data visualization pieces that can serve as exploratory and analytical tools. The course is part of a larger initiative, hosted by the Center for Spatial Research to teach courses in the critical use of digital tools across fields in architecture, urbanism, and the humanities.

TA
Time
Wed 6:30-8:30pm, Avery 114
General Topics
Students
Lecture Assignment
Jan 17

Syllabus overview
What is data viz?
What is code?
(slides)
 
Data Humanism by Georgia Lupi
Digital Networks, Public Spaces pp.14-15 DPS, Future Everything
P5.js Getting Started, Color
Intro–Chp.3 Braitenburg Vehicles (1986).
—
A0 Sharpie Instructions
A1.1 Helloworld: 1+2+3
Jan 24

Digital drawing 101: mental models
Web tech 101: servers, browsers, HTML, CSS, JS
Coding: version control, Github
(slides)
 
What is Code? Form + Code Chp. 1
Understanding Comics, Chp. 5,7,8 by Scott McCloud
Interaction of Color, Excerpts by Josef Albers
—
A1.2 Helloworld: add time
A2.1 Clocks: sketches (no code)
Jan 31

Programming 101: var, loop, if-else, functions
Coding: psuedocode, art of debugging
(slides)

 
Learning Processing: Chp. 4-7, 9, 11 by Shiffman, D.
(For reference: O'Reilly JavaScript book by Flanagan, D.)
—
A2.2 Clocks: choose three to code
Feb 7

Coding: strings, layout, JSON
Web tech 201: APIs
(slides)
 
Learning Processing: Chp. 8, 10, 17-19 by Shiffman, D.
Evolution of a Scientific American Graphic by Accurat Studio, 2016
Design and Redesign in Data Visualization by Viegas & Wattenberg
—
A3.1 Text: one dataset visualized two ways
Feb 14

Graphics: information hierarchy, states
Coding: mouse input, labels, forms
(slides)

 
The death of interactive infographics? by Baur, D.
In Defense of Interactive Graphics by Aisch, G.
You Say Data, I Say System by Jer Thorp
—
A3.2 Text: make one interactive
Feb 21

Graphics: visual variables reprise, perception
Inspiration: quantitative data viz
Coding: parse, format, collect data
(slides)
 
Learning About Your Data, Chp. 3 from Data Visualization by Kirk, A.
Finding Stories in Census Data, Source, E. Reyes
Bad Data Guide by Quartz data team
—
A4.1 Geography: 1 dataset, 3 layers, 1 coded
Feb 28

Multi-view interactives
Coding: state, animation, complexity
(slides)

 
The Architecture of a Data Visualization, Accurat Studio
The Whole Brilliant Enterprise, OCR.nyc
—
A4.2 Geography: multi-view interactive
Mar 7

Snow emergency—class cancelled
 
Nature of Code: Introduction by Shiffman, D.
In Theory and Practice Chp. 1 from Generative Art: A Practical Guide
—
A5 Generative sketch + 3 final ideas
Mar 14

Spring Break—no class
 
Mar 21 ☃️make-up: Mar 23 & Mar 24

Data biases: abstraction pitfalls, data collection
Perception biases: visual illusions
Code: concept review, state part 2
(slides)
 
What's the Point? Chp. 1 from Naked Statistics
The Well-Chosen Average, Chp. 3 from How to Lie with Statistics
The most misleading charts of 2015, fixed by Quartz
Artificial Intelligence’s White Guy Problem by Crawford, K.
—

A6 Misrepresentation
Mar 28

Sick day—no class
 

A7.1 Final: 3 proposals
Apr 4

Proposal pin-up
Narrative structure
Other viz tools (three.js, d3.js)
Examples and inspiration for final projects
(slides)
 

A7.2 Final: 3 dataset explorations
Apr 11

Dataset pin-ups
 

A7.3 Final: working prototype
Apr 18

Desk crits
 

A7.4 Final: polishes & documentation
Apr 25

Final Review, group A
Guest critics: Juan Francisco Saldarriaga, Arlene Ducao, and Chris Willard
 
May 2

Final Review, group B
Guest critics: Richard The, Daniel Scheibel