AANA18113U Data Governance: Ethics, Law and Politics - Summer 2019

Volume 2018/2019

Board of Studies, Department of Anthropology


The age of social big data brings with it a range of ethical, legal and political issues. From the ethics of protecting individual online privacy, to the legal frameworks regulating internet giants such as Facebook and Google, new data governance issues surface at a rapid pace. This course provides students with an introduction to key legislative, political and ethical principles and debates from the perspectives of anthropology, law, sociology, political science, and related disciplines, concerning the governance of data, needed for a range of analysis and management positions across private, public and non-profit organizations.

Data governance concerns the overall management of the availability, usability, integrity and security of data used in private, public and non-profit organizations. Comprehensive data governance addresses issues of data stewardship, ownership, compliance, privacy, data risks, data sensitivity and data sharing, including how such issues exist between different entities within the same organization. It involves thinking through issues such as: What do new forms of data-driven surveillance mean for relations between citizens, businesses and nation states, and how are new legal issues such as the legal basis for decision support systems and algorithmic decisions in public and private organizations addressed within current European legislation?

Students will be taught how to develop and implement ethically and politically informed procedures and infrastructures for organizing, managing and maintaining data and data products in public and private organizations. The course also introduces the most recent ethical and social-scientific models of data governance, including organizational models and risk assessments, and asks students to apply them to a real-world case of problem solving.

Casework takes students through the main phases of data governance analysis and practice: identification of a data-related problem and its internal and external stakeholders; analysis of how legal, technical-infrastructural and social-organizational components of the problem interrelate; pre-screening of possible solutions, including their respective risks; and final proposal and pilot check of a new data governance scheme expected to be robust in the face of foreseeable near- and mid-term challenges. By drawing on cutting-edge research in anthropology, law, sociology, and related disciplines, the students will also be able to contenxtualize and situate the case-based work within existing scientific debates concerning data governance and ethics.

The course is organized into three parts. First, we begin with an introduction to what can be done with social big data under current Danish and EU laws. This is followed by a consideration and discussion of what should (and should not) be done in more political and ethical terms. And finally, the course will discuss what could be done in terms of governance in different sectors of public administration (health, education, etc.), in the private business sector and in the non-profit sector.

Learning Outcome

At the end of the course, students should be able to



  • Explain and evaluate the quality of own as well as others' use of methods, datasets and analytical approaches in relation to the ethical, legal and political consequences of data governance.
  • Communicate and disseminate in writing and speech central questions around data ethics – academic as well as policy-oriented – with peers and non-experts.
  • Identify legal, ethical and political issues regarding a concrete data governance problem in an organizational context.
  • Design efficient, ethically and politico-legally sound procedures for organizing and maintaining data, including data stewardship, ownership, compliance, privacy, data risks, data sensitivity and data sharing.



  • Have a basic understanding of the ethical, legal and political aspects and consequences of the collection and use of social big data for a given administrative or commercial purpose.
  • Have an overview of key legal and social science (anthropology, sociology, etc.) concepts, ideas and debates pertaining to the use of social big data in private (profit and non-profit) or public contexts.
  • Account for the content and implications of national and EU legal frameworks for data collection, usage and storage (e.g. the EU’s General Data Protection Regulation).
  • Identify and reflect on key analytical steps and organizational procedures in data governance, from problem to solution.



  • Comply with and navigate existing legislation, rules and ethical frameworks for personal data management and governance, including the EU Personal Data Regulation (GDPR).
  • Critically assess possibilities and risks associated with uses of data in implementing data governance policies and rules in organizations and institutions based on ideas stemming from anthropology, law, political science and other social sciences.
  • Be competent in team-based work with a focus on organizational problem-solving vis-à-vis data governance challenges.
  • Have hands-on experience with concrete cases of data governance, including identification of problems, risk assessment, final proposal and pilot check of new governance scheme.

BSc-, Credit-, international students: 500 pages obligatory literature.

MSc students: 500 pages obligatory literature + 200 pages of literature chosen by students.


A combination of lectures, guest lectures, student presentations and group Work.
Students are not required to have prior knowledge of data legislation or public administration, nor are they expected to possess specialized social data science skills. A key prerequisite is an interest in the legal, political and ethical aspects and consequences of the increasing digitalization of both the public and private sectors (for-profit and non-profit), and a basic understanding of some social science theories and methods (e.g. ethnography, interviews, surveys, and/or policy-analysis).
  • Category
  • Hours
  • Class Instruction
  • 42
  • Exam
  • 40
  • Lectures
  • 95
  • Project work
  • 30
  • Total
  • 207
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
Peer feedback (Students give each other feedback)

The intermediate feedback will be peer-based, where groups provide feedback verbally to one another, in addition to short verbal feedback from the teacher(s). For the exam feedback, the teacher(s) will deliver approximately one page of feedback to the groups, outlining the strengths and weakenesses of the exam project paper.

7,5 ECTS
Type of assessment
Written assignment
Essay length: 21,600–26,400 keystrokes for an individual submission. 6,750–8,250 keystrokes per extra member for group submissions. The maximum number of students who can write an essay in a group is four.
All aids allowed
Marking scale
7-point grading scale
Censorship form
No external censorship

1. re-exam:

An essay with a revised problem statement must be submitted at the announced date. The students must sign up for the 1. re-exam.

Please note that the re-exam is an essay even for courses, where the ordinary exam is a portfolio exam.

2. re-exam:

A new essay with a revised problem statement must be submitted at the announced date next semester. The students must sign up for the 2. re-exam.

Criteria for exam assesment

See description of learning outcome.