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Data-driven Policymaking


Admission requirements

Students admitted to Public Administration Master, regardless of track affiliation. GOFS-students enrollment via study coordinator(s). Students from the LIACS-programme see other Prospectus page of this course.


New concepts try to grasp the way the public realm is working with big data, such as the ‘Data Readiness Concept’ and ‘Digital-era Governance’. They are built on the assumption that data- and technology-driven innovations in government need an infrastructure for creating value from data and closely linked to the e-government idea of technologies transforming government towards being more responsive and accountable. The course will unravel these more recent concepts and connect them to the existing concept of evidence-based policymaking and the literature on e-government and new public management. Taken together, these approaches to data-based policymaking carry different labels, but they converge on several themes. First, the idea that government entities require the capacity, skills and data culture to deal with this type of evidence. Second, the role of big data in policymaking, where government uses various information policy instruments for reaching policy goals. Finally, the idea that this data is used by government to engage citizens and digitise public services. These themes will be addressed throughout the course.

Course objectives

Putting the data movement in policy into the theoretical context of various existing research streams as well as contrasting the data-based promises with the reality of making data-driven decisions in the public sector by looking at concrete examples from the areas of infrastructure, climate change and healthcare. Analyse the opportunities and limitations of data in different policy sectors.


On the right side of programme front page of the Prospectus you will find links to the website and timetables, uSis and Brightspace.

Mode of instruction

The course contains a mixture of lectures, guest speakers, in-class group assignments and discussions. Interaction and discussions during class are based on the assigned readings that must be read in advance of the class.

Seminars: 12 hours
Self-study: 128 hours

Assessment method

Essay (30%)
Final Paper (70%)

Partial grades for this course can be compensated; the average of all partial grades for this course together must be at least 5.5.
Partial grades are only valid in the current academic year; partial grades will not remain valid after the exam and the resit of the course.

Reading list

Literature and additional information will be available on Brightspace two weeks before the start of the course.


Registration for this elective is possible via MyStudymap from t.b.a.. some courses and workgroups have a limited number of participants, so register on time (before the course starts).

For PA students: please register under 6454370 in Usis
For GofS students: there are limited spots available for GofS students please register via your studycoordinator

Register yourself via MyStudymap for each course, workgroup and exam (not all courses have workgroups and/or exams). Do so on time, before the start of the course; some courses and workgroups have limited spaces. You can view your personal schedule in MyTimetable after logging in.

Leiden University uses Brightspace as its online learning management system. After enrolment for the course in MyStudymap you will be automatically enrolled in the Brightspace environment of this course.

After registration for an exam you still need to confirm your attendance via MyStudymap. If you do not confirm, you will ultimately be de-registered and you will not be allowed to take the exam.
More information on registration via MyStudymap can be found on this page.

Please note: guest-/contract-/exchange students do not register via MyStudymap but via uSis. Guest-/contract-/exchange students also do not have to confirm their participation for exams via MyStudymap.


Dr. S.N. Giest