Simon Fraser University
Engaging the World

Course Outlines

Spring 2025 - CMNS 313 D200

Topics in Data and Society (4)

Critical/Applied Data Study

Class Number: 7248

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 6 – Apr 9, 2025: Mon, 2:30–5:20 p.m.
    Burnaby

  • Prerequisites:

    17 CMNS units with a minimum grade of C- or 45 units with a minimum CGPA of 2.00.

Description

CALENDAR DESCRIPTION:

Topics in the social, political, and cultural aspects of data and datafication. Explores social and philosophical implications of gathering, interpreting, and managing data. Topics include: data protection, visualization or sonification, data activism, big data, algorithmic bias and decision making, AI harms, big data, and the political economy of data. This course can be repeated once for credit (up to a maximum of two times).

COURSE DETAILS:

Topic for Spring 2025:   Critical/Applied Data Studies

What is data? How is data generated?  Classified?  Cleaned?  Stored?  “Cooked”?  What are machines “learning” from data?  What do machines “predict” from data?  Why does it matter for studies of media and communication?  Why does it matter for our contemporary political moment?

This course answers these questions by exploring the possibilities and limitations of a data-driven world.  We will unpack key concepts related to data in class and labs.  Students will explore a combination of primary texts and theoretical approaches that discuss data capture, storage, analysis, prediction, and their entanglements with knowledge formation and power in society.  They will examine the social world as it is currently shaped by data:  how data comes to govern realities, its political implications, and how we use data to imagine the future.  Students will also be introduced to case studies with hands-on data science labs to explore and expand on the theory learned in class.

This course will run in two physical settings: the first 1.5 hours will be in a CMNS seminar classroom, and the remainder will be in a CMNS computer lab where students will engage with data science tools to explore preliminary questions about the technical operation of data.  Students will use Google Colaboratory to program in Python and run data analysis.

No previous programming experience is required.

COURSE-LEVEL EDUCATIONAL GOALS:

  • Understand how theories related to data, computing histories, machine learning, and power relate to issues in contemporary communication technologies.
  • Introduce students to relevant terminology and basics of data analysis and data science.
  • Explore valuable tools to take on the ethical challenges of dealing with data in industry and academia.
  • Develop critical and creative thinking to rethink our relationships with data

Grading

  • Project - Proposal 5%
  • Project - Presentation 10%
  • Project - Final Submission 20%
  • Weekly Reading Responses 20%
  • Data Analysis Exercises 15%
  • Short Essay 15%
  • Participation (Seminar & Lab) 15%

NOTES:

The School expects that the grades awarded in this course will bear some reasonable relationship to established university-wide practices. In addition, the School will follow Policy S10.01 with respect to Academic Integrity, and Policies S10.02, S10.03 and S10.04 with regard to Student Discipline. For further information visit: www.sfu.ca/policies/Students/index.html

Materials

REQUIRED READING:

Readings will be made available on Canvas.

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html

RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.