Room: RCC-359A
Tuesday 9:00-12:00 / Section 021
Tuesday 15:00-18:00 / Section 011
Instructor: David Bouchard
Email: david.bouchard@ryerson.ca
Office: RCC-307
Office hours: Tuesday 13:00-15:00
Description
This class will explore the role of generative algorithms and database visualization approaches in New Media Art works. Processes of randomization, feedback, behaviour, mapping and emergence will be related to data and structure through the construction of interactive experiences. In particular, we will examine the social, cultural and political impact of data visualization through a discussion of contemporary and historical artworks as well as hands-on exercises. Students will deepen their understanding of presentation skills and professional practice through the development of individual works, including a final project.
Prerequisite: MPM27, MPM28
Technical skills
Some level of proficiency with programming using Processing as well as a basic knowledge of electronics and Arduino is assumed, however, some fundamental concepts will be reviewed during first weeks of class. While most of the in-class technical instruction for this course will be centered using Processing for accessing, mining, generating and visualizing data, the assignments and the final project will not be constrained to using Processing. With the instructor's approval, students are welcome and encouraged to explore other mediums and technologies as they see fit, as long as the project requirements are met and with the caveat that there will not be any in-class examples for these technologies.
Course Objectives
- Survey the state of the art in the fields of data visualization and generative art
- Develop the theoretical and practical foundations to explore this creative space
- Apply these learnings through the realization of a final project
Communication
Your Ryerson email will be the main method of communication for this class. Class announcements will be made over the BlackBoard system. You will also be required to maintain a class webpage where you will post your responses to the assignments.
Grading & Evaluation
5 - Participation
10 - Written responses
10 - Data Portrait
30 - Midterm project
45 - Final project
Late assignments will be deducted 15% per week, and will not be accepted beyond 2 weeks late. Final projects should be ready to be submitted on the due date, before we begin the scheduled critique. Late final projects will NOT be accepted.
This course represents one half of your overall production mark for
MPM35. Your final mark will be the average of the Fall and Winter
components of this course.
Participation
Participation is expected and required. You can demonstrate participation by being on time, doing the assignments, voicing your opinions in class and helping others. Failure to sign the attendance sheet will constitute an absence; 3 absences will be an automatic 0 for participation.
Written responses
Throughout the term, you will write 2 responses on your site to either a posted reading or a recommended artist talk or exhibition. Your responses should draw connections to material covered during lectures as well as your own practice. Each response should be between 300 and 500 words in length.
Other assignments
Details on the other assignments (including the final project) will be provided as their are posted on the course website.
Academic Conduct
Students are expected to follow the Student Code of Academic Conduct which can be found in the calendar or on-line at the Academic Council website: http://www.ryerson.ca/calendar/2011-2012/pg2030.htmlWith respect to writing programs, you are expected to create original works. Borrowing snippets of source code from various on-line resources is an accepted and wide-spread practice (assuming that the source code's licence allows it). However, make sure when doing so that you provide full references (URLs and name of original author) in your program's documentation for any borrowed code snippet.