Data science in public governance

Course goals

After completing the course, students can:

• apply design thinking methodology to identify, define, develop and test data-driven solutions for practical public governance issues;
• develop a technical prototype that is sensible in a public governance context;
• organize ethical reflection in applied data science projects and relate to public values;
• apply what is learned to formulate convincing value-sensitive policy advice which is based on data.

Assessment
Students are assessed as follows:

• group project report (50% of the final mark)
• group presentation (10%)
• written exam on theory (40%)

To qualify for a repair of the final result the mark needs to be at least a 4, or “AANV”.

Content

Do you want to use data science in a practical way to directly address real-world issues facing your community ?

In this course, through a combination of lectures, discussions and hands-on practically applied data analysis in a real-world project, you will gain the skills needed to use data science to make a difference in your community.
You will explore the intersection of data science and public governance, learning how data can be used in shaping and evaluating public policy, improving public service delivery, and enhancing transparency and accountability.
You will develop an understanding of public governance and the importance of critical reflection on novel data technology in the public domain. You will use, for example, the Code of Good Digital Public Administration.

In parallel, you will work on a hands-on data science project in the context of public governance throughout this course.
You will, for example, analyze datasets to aid understanding of a societal issue or facilitate dissemination of complex information utilizing a Large Language Model (LLM) in combination with Retrieval-Augmented Generation (RAG).
In this real-world project, you will:

• actively participate in public government events (town halls, municipality meetings) to identify a pressing societal issue.
• analyze relevant open government data to understand the chosen issue.
• utilize the iterative Design Thinking cycle (empathize, define, ideate, prototype, test) to develop a data-driven solution that can contribute positively to a real-world societal issue.
• develop a technical prototype of your data science solution, for example, an LLM (Large Language Model) to unlock large governmental open data sets to the public
• test your solution with citizens directly affected by the issue and refine your ideas based on their feedback.
• present findings and recommendations to relevant stakeholders, such as council members.
• use responsible data practices, ensuring transparency and accountability throughout the process.

Course form
The main teaching method is project-based, in addition to:

• (guest) lectures
• a tutorial on design thinking
• individual and group assignments
• practical work (e.g. analyzing open data, finding and code signing with stakeholders, developing a technical prototype, etcetera)

Additional information

Enrolment in this course is only available by using the pre-enrolment form that will be forwarded to all ADSM students in the second week of September.