Kies de Nederlandse taal
Course module: 620087-M-6
Data Science Regulation & Law
Course info
Course module620087-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg Law School; Law, Technology, Markets and Society;
Is part of
M Communication and Information Sciences
M Data Science and Society
Contact M.H.M. Schellekens
PreviousNext 1
prof. dr. R.E. Leenes
Other course modules lecturer
mr.dr. L.A. van Noorloos
Other course modules lecturer
Coordinator course M.H.M. Schellekens
Other course modules lecturer
mr. F. Schemkes
Other course modules lecturer
Lecturer T.F.E. Tjong Tjin Tai
Other course modules lecturer
Academic year2018
Starting block
SM 1
Course mode
RemarksThis information is not up to date. Check the Course Catalog 2019 or select the course via “Register”.
Registration openfrom 13/08/2018 09:00 up to and including 31/07/2019
The key objective of this course is to make students aware about the role law plays in the field of data science.
After successfully completing this course, students should be able to:

Cluster 1: Introduction to law and data science
·         The student can identify the basic functions, sources and actors in law.
·         The student can describe the relation of law to different modalities of

Cluster 2: Private Law and data science
·         The student can explain and apply basic concepts of private law, such as the distinction between claims based on property right, contract, and tort,
          the assessment of unfair general contractual terms, contracting on use and transfer of data, and remedies in contract and tort.

Cluster 3: Public/administrative and criminal law and data science
·        The student can explain the role of general administrative law as well as more specific administrative regulations on information management in relation to data   
·        The student can explain basic concepts of criminal procedural law (such as the difference between inquisitorial and adversarial systems, the different actors and
          phases in criminal procedure, and the role of several fundamental rights in criminal procedure) and apply these to data science applications.

Cluster 4: Intellectual Property Rights and data science
·         The student has a basic understanding of patent law, copyright law and database protection in the EU.
·         The student can critically reflect on the application of IP law to data and technologies and its implications for innovation in data science.

Cluster 5: Ethics
·         The student can describe the relation between the law, ethics, and ethical theories.
·         The student can compare different ethical outlooks, the corresponding ethical theories and apply the latter to ethical questions involving data science.
This course provides an introduction to the role of law with regard to data science. The course is designed for students with very limited or no background in law. Law can be seen as rules that limit people’s freedom of action. However, a legal system encompasses way more then merely a set of rules. Rules are developed by public and private institutions, the system involves processes and actors for control and includes police forces and courts to enforce the rules and resolve disputes. The course is divided into 5 clusters. The first cluster provides a general introduction into Law. The other clusters cover a specific legal domain or address the relation between law and ethics. Besides covering the basics of legal science – both in general and in the dominant legal domains: private law (including intellectual property law), public law and criminal law - the course reflects upon specific legal issues pertaining data science business developments on the basis of examples and a case/scenario. This case/scenario forms the common threat of the course, linking together the domain specific issues relevant when engaged with (the development of a) data science business. This course will not delve into the distinct and important legal area of data protection as this is core to the elective course “Data science: sustainability, privacy and security”.
The course is structured in five distinct clusters:
Cluster 1: Introduction to law and data science
Cluster 2: Private Law and data science
Cluster 3: Public /Administrative and criminal law and data science
Cluster 4: Intellectual Property Rights and data science
Cluster 5: Ethics in data science

Type of instructions
Interactive Lectures
Type of exams
- Written Block Exams + Resit option
- 5 Assignments + Resit option (the assignments are your entry ticket to the written block exams)

Timetable information
620087-M-6|Data Science Regulation & Law
Written test opportunities
Written test opportunities (HIST)
Schriftelijk / WrittenEXAM_01SM 1117-12-2018
Schriftelijk / WrittenEXAM_01SM 1221-01-2019
Required materials
To be announced
Will be announced via Blackboard
Recommended materials


Kies de Nederlandse taal