How can governments become more open and transparent, while simultaneously dealing with various challenges, such as data sensitivity? How can open government data be used to improve policy making? Which technologies are available to make governments more open and to use open government data? How can data be turned into smartness?
Governments all over the world aim to become more open and transparent in order to establish closer ties with their constituents. However, opening government involves complex challenges and poses two major areas of concerns. First, many different stakeholders are involved and there are various dependencies between them, and second, the technologies that support open government are fragmented. In addition, it is unclear how different contexts should alter the best practices for open government.
This course explores the foundations and objectives of Open Government and examines current developments, including the opening and reuse of governmental data such as the release of data by governments in America and Europe.
This course will empower you, by helping you grasp the key principles surrounding open government. The topics of the course are applied to concrete cases, which you will be asked to analyze and discuss with your peers.
This course may be of interest to the following:
- Students interested in the basics of open government, in smart government, in data-driven governance and data-driven research.
- Professionals and researchers working on open government research and interested in strategies and challenges for opening governments.
- Professionals and researchers working on open data research or open data initiatives.
- Professionals and researchers working on topics related to public values, use of algorithms, including transparency and privacy, in a governmental context.
- Senior administrators, policy advisors, government officials or agency members, who are interested in how ICTs change governments and how ICTs can be used in public administrations.
What you'll learn
- Basic concepts related to Open Government and Open Government Data.
- How to analyze and discuss benefits, barriers and potential negative effects of a particular open government case.
- How to analyze public values and best practices related to open government.
- How to make use of open data using algorithms and artificial intelligence techniques.
- How to apply the open government principles in various situations.
- How to understand potential negative and positive effects Open Government might bring to the workplace.
Course SyllabusWeek 1: Introduction to Open Government
Introduction to the foundations and objectives of Open Government, including its meaning, ICT-developments that influence(d) Open Government and stakeholders of Open Government.
Week 2. Opening and reusing government data
An introduction to concepts related to Open Government Data (e.g. a definition of Open Government Data, using open data for policy making, and open data portals and infrastructures) and to benefits, barriers and potential negative effects of open government data cases.
Week 3. Technical and judicial aspects of governmental information sharing
A discussion of real open government cases and an analysis and discussion of benefits, barriers and potential negative effects of open government cases, including technological and judicial aspects (e.g. metadata and technologies for linking big and open data).
Week 4. Open government and public values and conclusions
An analysis and discussion of public values and best practices related to open government. In this week we also discuss transparency and privacy in the context of open government.
Week 5. Exam
In this week, students complete their final assignment and exam.
Unless otherwise specified, the Course Materials of this course are Copyright Delft University of Technology and are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This is a Massive Open Online Course (MOOC) that runs on edX. Basic knowledge of information and communication technology is required, as well as basic knowledge of multi-actor systems.