Instructor: Roopa Vasudevan
Email: roopa.vasudevan@nyu.edu
Office Hours: By appointment. Please send me an email with three good times for you, and I will send you a calendar invite and Zoom link.
Class Resident: Ellen Nickles
Email: ellen.nickles@nyu.edu
Office Hours: Mondays, 8am-10am EST Sign up here
Course Discord Channel: #local-data
Etherpad for 8AM ET section: https://board.net/p/local-data-am
Etherpad for 8PM ET section: https://board.net/p/local-data-pm
This course will approach data collection as a local, situated and contextually-bound process, and ask what it means to examine large-scale social issues from a close, specific perspective. Starting from the observation that data is never collected omnisciently or neutrally, students will explore questions of power, context, and knowledge production through reading, discussion, and practical exercises in data collection and representation using both computational (primarily web-based and JavaScript) and analog methods. Students will be asked to work in teams (at a distance) for the first half of the semester to produce a project design that addresses an issue of common interest. This will require them to engage in collaborative problem solving and collective inquiry, and to take care to emphasize reflexivity and an awareness of their own participation in their creative processes. Potential areas of focus, such as the environment, education or social justice, will be relevant at a global scope but accessible at a local scale. As such, students will be required to identify and leverage salient points of contact at their respective locations as well as integrate local insights and fieldwork into their projects.
By the end of this course, students will be able to:
- Critically engage with theoretical concepts surrounding data collection, analysis and representation;
- Practically engage these concepts in creative work;
- Design a data collection project that takes local environment and context into consideration;
- Understand how positionality contributes to knowledge production, and speak to the ways in which their own situated identities impact the ways in which their work has been constructed.
This is a 7-week class containing both a theory and practice component. Students will be expected to critically engage with scholars considering data collection, analysis and representation through reading and class discussion. They will then apply these ideas to their own creative process, working in teams to craft a design proposal for a data-based project that draws from their own specific locations and contexts. Students will be expected to work closely with their partner over the course of the class, submitting three (3) of four (4) smaller assignments as collaborative efforts.
There will also be class time devoted to technical demonstrations on web-based data visualization. There will be one (1) web-based project produced as part of this class; however, students are not required to use Internet or computational technologies in their final project design, and instead are encouraged to consider a creative output that is most appropriate for the data source they intend to utilize for the work.
This course will require a significant amount of reading each week. These readings will serve as the foundation of the class, and will inform the practical work that students undertake. While none of the individual readings will exceed 20-30 pages in length, there will usually be several placed together in order to spark conversations between the texts and to illuminate convergences and divergences in thinking. Students are expected to come to class having done all assigned readings, and with one (1) question prepared that they would like to bring to the group for discussion.
There will be four (4) small assignments due as part of the class. Three (3) of these assignments will serve as scaffolding for the final project. These assignments are as follows:
- Analog data collection exercise: Students will individually collect data in an analog format. Documentation for this can include (but not limited to) photographs, journal entries or drawings; the only guideline is that students cannot use any kind of computational process in order to complete this assignment.
- Project idea: In teams of two (2), students will submit a 1-page document outlining their final project idea to be workshopped by the rest of the class.
- Sample data source: Students will submit a sample of the data they are planning to use for their final project.
- Web-based exploration of project: Students will begin to explore their data using web-based tools such as d3 and p5.js.
All assignments should be submitted by the beginning of class on the day they are due.
Final (project design): Students will be expected to complete a detailed project design proposal for this course, including evidence of work done towards a prototype. The guidelines for this project are extremely broad—these can range from a fully analog installation, to an extension of the web-based exploration. However, students must work in assigned pairs for this project, and the project must engage a data source that is local and specific to one or both students’ locations. The project must also contextualize the use of the data within the project’s overall goals.
Class participation: 35%
Analog data collection exercise: 10%
Scaffolding assignments for final: 25%
Final project design: 30%
Plagiarism is presenting someone else’s work as though it were your own. More specifically, plagiarism is to present as your own: A sequence of words quoted without quotation marks from another writer or a paraphrased passage from another writer’s work or facts, ideas or images composed by someone else.
The core of the educational experience at the Tisch School of the Arts is the creation of original academic and artistic work by students for the critical review of faculty members. It is therefore of the utmost importance that students at all times provide their instructors with an accurate sense of their current abilities and knowledge in order to receive appropriate constructive criticism and advice. Any attempt to evade that essential, transparent transaction between instructor and student through plagiarism or cheating is educationally self-defeating and a grave violation of Tisch School of the Arts community standards. For all the details on plagiarism, please refer to page 10 of the Tisch School of the Arts, Policies and Procedures Handbook, which can be found online at: https://tisch.nyu.edu/student-affairs/important-resources/tisch-policies-and-handbooks
Please feel free to make suggestions to your instructor about ways in which this class could become more accessible to you. Academic accommodations are available for students with documented disabilities. Please contact the Moses Center for Students with Disabilities at 212 998-4980 for further information.
Your health and safety are a priority at NYU. If you experience any health or mental health issues during this course, we encourage you to utilize the support services of the 24/7 NYU Wellness Exchange 212-443-9999. Also, all students who may require an academic accommodation due to a qualified disability, physical or mental, please register with the Moses Center 212-998-4980. Please let your instructor know if you need help connecting to these resources.
Laptops will be an essential part of the course and may be used in class during workshops and for taking notes in lecture. Laptops must be closed during class discussions and student presentations. Phone use in class is strictly prohibited unless directly related to a presentation of your own work or if you are asked to do so as part of the curriculum.
Tisch School of the Arts to dedicated to providing its students with a learning environment that is rigorous, respectful, supportive and nurturing so that they can engage in the free exchange of ideas and commit themselves fully to the study of their discipline. To that end Tisch is committed to enforcing University policies prohibiting all forms of sexual misconduct as well as discrimination on the basis of sex and gender. Detailed information regarding these policies and the resources that are available to students through the Title IX office can be found by using the following link: Title IX at NYU.