- Instructor: Genevieve Hoffman
- Instructor e-mail: [email protected]
- Office Hours: Fridays, 2pm – 4pm. Sign up on google calendar
- Class Logistics: Mondays, 9am – 11:55am
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 tools (such as D3.js, Leaflet.js, OpenRefine, MapBox & CartoDB).
This course will be divided into four 3 week '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 run for three classes. The first of the three classes will involve a survey of work being done in this area, and a 'workshop' teaching one or two important technical points. The second class will involve a discussion around assigned readings and a review of available tools. The third class will feature a guest speaker, and brief (5 minute) 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:
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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?
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Realized projects will be built in the two weeks between assignment and the due date. They will 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
- The Anti-Sublime in New Media, Lev Manovich
- 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 derived from a data set
- Due Week 3, September 25th. Documentation should be posted and a link emailed before class begins
September 11th – Week 1. The lay of the land - slides shown in class
September 18th – Week 2. Discussion of readings & technical workshop (Processing) - slides shown in class
September 25th – Week 3. Guest Speaker (Mona Chalabi) & Project presentations
Readings:
- Deconstructing Information, Lee Thayer
- Consider the Boolean, Jacob Harris
- On a Collections as Data Imperative, Thomas Padilla
- A Sea of Data: Apophenia and Pattern (Mis-)Recognition, Hito Steyerl
October 2nd – Week 4. Topic survey & technical workshop (RiTA) - slides shown in class
October 9th - Fall break
October 16th – Week 5. Discussion of readings & overview of other resources - slides shown in class
October 23rd – Week 6. Guest Speaker (Matt Daniels) & Project presentations
Readings:
- On Space and Spatial Practice in Contemporary Geography, Michael R Curry
- 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 7. Topic survey & technical workshop (Leaflet.js / Mapbox GL) - slides shown in class
November 6th – Week 8. (Rescheduled to November 8th, 9am) - Discussion of readings & overview of other resources - slides shown in class
November 13th – Week 9. Guest Speaker (Dave Riordan) & 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 10. Topic survey & technical workshop (D3) - slides shown in class
November 27th – Week 11. Discussion of readings & overview of other resources - slides shown in class
December 4th – Week 12. Guest Speaker (Shannon Mattern) & Project presentations