- Instructor: Genevieve Hoffman
- Instructor e-mail: ghoffman@nyu.edu
- Office Hours: Fridays, 4:30 – 6pm. Sign up on google calendar
- Class Logistics: Tuesdays, 6:30 – 9pm
Fascinating and terrifying things are happening at the intersection of data and culture. Our lives are being constantly measured, and information about us is being surveilled, stolen, and commodified. Dialogue around this data revolution has been dominated by corporations, governments, and industry - but what about the arts? In this class, we’ll investigate the means by which artists can engage (and are engaging) in the collection, processing, and representation of data. Using a research-focused, prototype-based approach, we’ll build a series of collective and individual projects to interrogate the ‘new data reality’. Students will use Processing, along with a variety of analog media or open-source data and visualization tools (such as D3.js, OpenRefine, MapBox, Mappa and THREE.js).
This course will be divided into four 'sections', each focusing on a different aspect of data art:
- Data & Aesthetic
- Text, Archives & Memory Stores
- Data & Publics
- Ethics, Humans & Responsibility
Each of these sections will begin with an introductory survey of work being done in this area, and a 'workshop' going over a few important technical points. The next class(es) will involve a discussion around assigned readings and a review of available tools, code libraries, and techniques. The last class in a section will feature a guest speaker, and brief (5 minute max) presentations of project work (see below).
For each of these sections, you will complete a small project, which will be assigned on the first day of the section and will be due on the last. The first assignment will be individual and realized. For the last three assignments, you have the choice of doing a conceptual project, or a realized one:
-
Conceptual projects should be focused on possibility without constraint. What would or could you build if you were not restricted by materials, budget, technological possibility, or coding skills? The deliverable is a project proposal, much as you might submit for an art funding grant, or to a client pitching a potential project. Both written and visual descriptions of the project are required, and you may include audiovisual samples as well if that's helpful for getting the idea across.
-
Realized projects will be built in the 2-3 weeks between assignment at the end of the section's first class and the due date. They should be posted to this repo with source code if applicable, and written up with a blog post.
For the last three assignments, each student will be required to complete one conceptual project, and two realized projects. It is your choice as to which of the last three sections you choose for which.
The first project is required to be an individual project. For the last three assignments, the project can be done as an individual project, or in groups of up to three students. Each student will be required to do at least one group project.
You can expect to have 3-4 assigned readings for each thematic section. You must complete all readings prior to class, and come ready to participate in discussion. Projects must be posted to this GitHub repo in the appropriate folder, along with source code (where applicable) before the start of class when the assignment is due. A brief blog post about the project is also required to be completed before the start of class.
If we were using a percentage-based grading system, the numbers would look something like this:
Class participation: 30% Semester Projects: 70% Since we’re not using a percentage-based grading system, let me put it another way: if you’re an active contributor to our discussions in class, and you complete your assignments, and you make something ambitious/excellent as a final project, you’ll pass this class. If you don’t, you won’t.
(i) Everyone shows up to class on time. If you’re going to be late, let me know in advance. If you need to miss a class for a real reason, you must also let me know in advance.
(ii) Everyone does the readings. For the most part, they’re short, fun, and useful. Students will be responsible for leading class discussion on readings on a rotating basis.
(iii) All assignment work is due at the beginning of class. Everyone gets a free pass for one late assignment. After that, any assignments not ready for the start of class will be counted as incomplete. A completed blog post about each assignment is required.
(iv) Everyone in the class must attend office hours at least once in the first three weeks of class.
(v) We’ll have a series of guest speakers coming into class over the course of the term. I will provide resources to learn about their work prior to their visits – everyone in class must do their homework and be prepared to learn from our guests.
(vi) I am 100% dedicated to an inclusive, harassment-free experience for everyone regardless of gender, race, sexual orientation, disability, background, appearance, or religion. I will not tolerate harassment of class participants in any form.
(i) Gary Shteyngart - Super Sad True Love Story
(ii) Brian K. Vaughan, Marcos Martin and Muntsa Vicente - The Private Eye - http://panelsyndicate.com/comics/tpeye
Readings:
- A Concise Taxonomy for Describing Data as an Art Material, Julie Freeman, Geraint Wiggins, Gavin Starks and Mark Sandler
- What Would Feminist Data Visualization Look Like? Catherine D'Ignazio
- DataViz - The UnEmpathetic Art, Mushon Zer-Aviv
- Picturing the Self in the Age of Data, Dan Weiskopf
Watch:
- Subtle Data, Stefanie Posavec speaking at the 2013 Eyeo Festival
- How I Learned to Love Data Visualization (Again), Jon Schwabish speaking at the 2015 Visualized Conference
Assignment:
- Data (Self)Portrait: Create a self-portrait or portrait of someone else. The portrait must be derived from a data set, or use data as a material.
- Due Week 4, September 25th. Documentation should be posted and a link emailed before class begins
September 4th – Week 1. The lay of the land & introductions - slides shown in class
September 11th – Week 2. Topic Survey & technical overview (data translation) - slides shown in class
September 18th – Week 3. Discussion of readings & technical workshop (ES6 Intro) - slides shown in class
September 25th - Week 4. Guest Speaker (Brian House) & Project presentations
Readings:
- Consider the Boolean, Jacob Harris
- On a Collections as Data Imperative, Thomas Padilla
- A Sea of Data: Apophenia and Pattern (Mis-)Recognition, Hito Steyerl
- Abundant Images and the Collective Sublime, Kate Palmer Albers
October 2nd – Week 5. Topic survey & technical workshop (RiTA) - slides show in class
October 9th - NO CLASS, Legislative Day
October 16th – Week 6. Discussion of readings & overview of other resources (puppeteer.js) - slides shown in class
October 23rd – Week 7. Guest Speaker (Roopa Vasudevan) & Project presentations
Readings:
- Rethinking Maps: Thinking about Maps, Rob Kitchin, Chris Perkins & Martin Dodge
- Here Be Dragons: Finding the Blank Spaces in a Well-Mapped World, Lois Parshley
- Mapping’s Intelligent Agents Shannon Mattern
- IMG MGMT: The Nine Eyes of Google Street View, Jon Rafman
October 30th – Week 8. Topic survey & technical workshop (Web Maps / Public Data) - slides shown in class
November 6th – Week 9. Discussion of readings & overview of other resources (Leaflet.js / Mapbox GL / Mappa + p5.js / Turf.js) - slides shown in class
November 13th – Week 10. Guest Speaker (Mahir Yavuz) & Project presentations
Readings:
- Critical Questions for Big Data, danah boyd & Kate Crawford
- Big data problems we face today can be traced to the social ordering practices of the 19th century, Joanne Travaglia & Hamish Robertson
- A chronology of tactics: Art tackles Big Data and the environment, Brooke Singer
- You Say Data, I Say System, Jer Thorp
November 20th – Week 11. Topic survey & overview of the landscape - slides shown in class
November 27th – Week 12. Discussion of readings & Color + Data Visualization & D3 - slides shown in class
December 4th – Week 13. Technical workshop (THREE.js / Unity) - slides shown in class
December 11th - Week 14. Guest Speaker (Brooke Singer) & Project presentations