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Data for Peace and Justice

Vak 2017-2018

Admission requirements

None.

Description

How could the ever-growing amounts of digital data help us to confront today’s complex societal challenges? Will more data allow us to improve policy responses in the domains of development and humanitarian action? Could Big Data help us to end violent conflicts and build peace?

Big Data has often been described as a fuel for both innovation and our economy. It is being applied in many areas, for example financial markets, health and the intelligence sector. It is however foreseen that the increased availability of new data sources offers new opportunities in other domains as well. In this course, you will explore current trends and prospects for Big Data to become a drive for peace and justice.
Lectures will reflect on various showcases, including the use of open web data and social media for monitoring conflict dynamics in Syria; the analysis of mobile phone data in analysing epidemic outbreaks such as Ebola; and the availability of various data sources in confronting the current refugee crisis. You will focus on the challenges both from a policy and responsible innovation perspective

Course objectives

At the end of this course the participants will:

  • assess complex societal challenges within the domains of development, humanitarian action as well as peace and justice;
  • analyze the interests and relevance of different stakeholders within a case of development, humanitarian action as well as peace and justice;
  • explain the concepts of big data and data-driven innovation;
  • conduct a benchmarking and review of relevant case studies on data-driven innovations in the domains of development, humanitarian actions as well as peace and justice;
  • determine whether and how data might inform policies in confronting complex societal challenges;
  • reflect both on the opportunities as well as challenges to operationalizing data to tackle a complex societal challenge;
  • evaluate the risks and harms in using data from a responsible use and innovation perspective;
  • build an argument and present it based on a case, in writing.

Timetable

timetable

Course outline

During this course you will be provided with the following lectures:

  • Week 1: Introduction to complex societal challenges [together with S. Louwaars]
  • Week 2: (Big) Data, Big Promise
  • Week 3: Data-Driven Innovation for Peace & Justice
  • Week 4: Innovators for Peace & Justice: Trends & Challenges [panel session]
  • Week 5: Introduction to Data Responsibility
  • Week 6: From Ideas to Action
  • Week 7: Wrap Up and Assignments

Mode of instruction

Course Load

Assessment method

Assessment

  • Essay: write and publish an essay on the potential of Data for Humanity (max 2.500 words). You will reflect on the importance of data-driven innovations for confronting a complex societal challenge within the domains of development, humanitarian action or peace and justice. This will be done from the perspective of a challenge owner within one of these domains;
  • Video assignment: students will make a 3-minute video in which they will present the most important conclusions and recommendations of their essay assignment;
  • Participation: be present and engage in all sessions; publish your research on collaborative research platform in an accessible manner for other students and external stakeholders; and give a presentation of your work for a larger audience.

Weighing

  • Essay: 70%
  • Video assignment: 30%

Resit

The students are allowed one re-sit per examination. It is not allowed to re-sit an examination or assignment for which they have received a pass (6,0 or higher). It is allowed to re-sit an examination or assignment which they haven't done during the first occasion. The re-sit format needs to be discussed with the teacher of the course in line with examination regulations.

In case the student is granted an extra re-sit by the Board of Examiners, this re-sit has to take place within study year 2017-2018. This means the students have to complete the minor within one study year.

Exam Review

Attendance

All students have to be present in all modules, including the Skill Labs. The teachers and the minor coordinator have to be notified in advance for the absences.
For each absence, students have to do an assignment. The students who are absent more than twice will not pass the module.

Blackboard

In this course, Blackboard is used to present course information, notify you of changes to the course and to make course materials available.

Reading list

Scientific and professional papers and teaching cases, to be provided or indicated via Blackboard.

Registration

You register for the whole minor and for each individual course in uSis.

Contact