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Digitalization, Data and Governance I: Integrative project Data for policy and decision-making


Admission requirements

This course is only available for Bachelor Public Administration students (DDG).


This course integrates knowledge and skills from two first year courses: The Digital State and Data Science Skills and Applications 1. The course achieves this by guiding students to develop their own group project/research. During the development of their projects, students will approach the concepts, theories, and challenges associated with the development of the digital state, and how data analytics are (or can be) used to help the government work better. In other words, students will learn how the processes and systems of the digital state can be ‘hacked’ and improved via an evidence-based approach. Students can develop their own projects with a variety of perspectives, ranging from proof-of-concept tools using their acquired theoretical grounds and programing skills, to addressing the impact of data analytics in Data State.

Course objectives

By the end of the course, students will be able to:

  • Use scholarly literature and policy information to approach a research problem about the digital state.

  • Plan and deliver a design/project by conducting teamwork, leveraging project management and communication skills.

  • Understand the practical implications on the public sector of computational programming tools and manage those tools in a way to identify the policy problems and create positive change.

  • Effectively communicate the design, results, and conclusions of the project, to both specialized and non-specialized audiences.


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

Mode of instruction

The course has a mixed lecture approach, with a high practical orientation. A part of the course will be based on lectures, working groups and tutorials, that will guide the students integrating the knowledge and skills from The Digital State and Computational/Digital skills 1: Data - uses and opportunities courses to craft their own research/projects. But a very important part of the course will rely on self-study and group teamwork.

Total study load: 140 hours, of which:

Lecture, tutorials & working groups: 16 hours (Lecture: 2 hour, tutorial 2 hour, working group 12 hours)
Self-study: 124 hours

Assessment method

Individual assignment:

  • Literature review (20%)

Group assignments:

  • Short research/project proposal (20%)

  • Paper presentation (pass/fail)

  • Final paper submission (60%)

There will be one individual assignment regarding practicing literature review. And most assignments are group-based. Students should attend all lecture, tutorials, and working group meetings. The working group meetings are mandatory. Students must show that they have participated actively in their group. All workgroup assignments must be submitted on time on Brightspace.
The proposal assignment can compensate for the final paper assignment. To pass the course, students must present their group project in class and the grade for the final paper must be at least 5.5. Retake for the final paper assignment is allowed but the resubmission will receive score with a maximum grade of 7 due to the principle of fairness.

Partial grades are only valid in the current academic year.

Reading list

This course mainly builds on literature from the following first year courses: The Digital State and Computational/Digital skills 1. Additional articles may be shared in the course guide and on Brightspace. Articles should be studied prior to the sessions.


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.

Registration for this course is possible from Tuesday 12 December, 13:00 h.

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.

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.


Dr. Hsini Huang: