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860-0026-00L 3 Credits MSC D-GESS

Data Practices

Lecturers & Examiners: Prof. Dr. Matthias Leese
Number of participants limited to 20. Priority for Science, Technology, and Policy MSc and PhD students.
VVZ CR n/a

Last Updated: 2026-02-05 16:02:18

Abstract

The aim of this course is to establish an understanding of data as embedded in social contexts. Studying data from a social scientific perspective is necessary to account for these influences and analyze the ways in which data practices shape the ways in which data allow us to see and modify the world.

Objective

At the end of the term ,students will be able to:  reflect concepts and theories of data practices and situate them within wider social science contexts  identify key actors, sites, and domain contexts of data practices  choose appropriate ways and methods to study data practices empirically

Content

The aim of this course is to establish an understanding of data as embedded in social contexts. Data do not exist independently of the ideas, instruments, contexts and rationales used to generate, process, and analyze them. They are not neutral representations of external realities, but they are imbued with political and economic interests, cultural norms and tacit assumptions. Studying data from a social scientific perspective, it is thus necessary to account for these influences and analyze the ways in which data practices shape the ways in which data allow us to see and modify the world.

Resources

Lecture Notes

Course materials are provided on Moodle.

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Grading(1) Active and qualitatively high-level participation in class discussion based on thorough study of the texts;preparation of assignments (20%)(2) Seminar Paper (80%)Seminar PaperStudents will be required to hand in a seminar paper that, based on the course contents, engages data practicesfrom an empirical or theoretical perspective. The paper should not exceed 6.000 words (includingreferences) and adhere to academic formatting and citation standards

Registration & Places

Max Places
20
Priority: Registration for the course unit is until 09.09.2022 only possible for the primary target group

Course Components

Type Title Time & Place Hours
seminar Data Practices
  • Mon 12:15-14:00 (IFW C 31)
2 h weekly

Offered In