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, Yuliya Parshina-Kottas, TBD