Prospectus

nl en

Data-driven Policy Making

Course 2018-2019

Admission requirements

none

Description

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 digitize 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.
• ICT in Business Students: Gain an understanding of how data is utilized in the policy-making process.
• MPA Students: Analyze the opportunities and limitations of data in different policy sectors.

Timetable

The schedule can be found on the Leiden University student website

Detailed table of contents can be found in blackboard.

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.

Course Load

• Seminars: 18 hours
• Self-study: 70 hours
• Assignments: 49 hours

Assessment method

Essay (30%)
Final Paper (70%)

Blackboard

blackboard

Reading list

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

Registration

You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.

There is only limited capacity for external students. Please contact the programme Co-ordinator

Contact

Programme Co-ordinator: ms. Esme Caubo

Course Co-ordinator: Dr. Sarah Giest

Remarks

Also register for every course in Blackboard. Important information about the course is posted here.