Intertwining Data, Discourses, and Politics in Environmental and Population Science.

How do narratives shape the world around us? How are data used (or not) to feed these narratives? This course will equip you with a combination of technical skills, such as (creative) data visualization, and theoretical knowledge about common scientific and political narratives on environmental and population issues.

Focusing on these topics, we will learn how to identify narratives in scientific papers or in the media. What data were chosen in the first place? By whom? How are the data contextualized and visualized to feed a particular narrative? Taking inspiration from the principles of Data Feminism (D’Ignazio and Klein, 2020),  we will identify problematic aspects of mainstream use of data that support dominant narratives and then delve into how data science can be used to challenge hierarchical power structures and address structural inequalities. We will also explore the potential of creative data visualization to create compelling narratives.

Throughout the course, we will explore topics such as:

Theoretical insights:

o The landscape of environmental discourses

o Principles of Data Feminism (D’Ignazio and Klein, 2020),

o Population discourses and their political significance (population and climate change, population and women’s health movement, neo-malthusianism etc)

 

Practical skills:

o Introduction to R programming and data processing

o Basics of data visualization

o Artistic approaches to data visualization

o Exploration of alternatives to visualization such as sonification or other sensory media.

• Regular attendance
• Active participation in discussions
• At the end of the semester, you will create a small data visualization project using an artistic medium and/or a data visualization software. Alongside this visual representation, you will write a short essay that elucidates the narrative behind the data, frames the issues involved, and offers a critical reflection on the various discourses associated with the data.