The EU and International Security - Data processing and analysis

Sciences Po Grenoble - School of European Governance
Major Track in European Governance
4th   year  -  2018-2019


Mayeul Kauffmann (Chercheur principal CYBIS - UGA, CESICE)
Fanny Coulomb (Maître de conférences Sciences Po Grenoble)


This course aims at getting a better knowledge of some issues related to the external security of European countries, with a focus on defense industries, arms trade and the risk of armed conflict, emphasizing the methodologies and software tools which can help in the analysis of these topics.

The presentation of the software tools will be, jointly, theoretical, applied to current issues, interactive and practical. Processing and analysis of real data using dedicated software will be carried out. Teaching will be done in a way that will allow the students to reuse many of the concepts and techniques learned to process and analyse related data to other aspects of international affairs.
Among the main topics, the European Defence Technological and Industrial Base (EDTIB), arms transfers from and to Europe, embargoes and arms controls, as well as the risk of armed conflicts, will be covered.
The relationship between these topics will be thoroughly assessed using available data; for instance, to what extent analysis on the risk of armed conflicts can fuel decisions on embargoes and controls to arm transfers from European arms producers.
Practical introduction to various software tools will be done, including for the management and analysis of statistical data (statistical package), the processing of geospatial information (Geographical Information System) and textual information (natural language processing).

Skills learned

By the end of the course, students will have acquired knowledge on the following points:
1. Current security analyzes, from a political and economic perspective;
2. Statistical models used in studies on international security ;
3. Existing databases that can be used for analysis in security-related areas;
4. Statistical and IT tools that can be used to process empirical data;
5. The use of software (free and open-source) to process and analyse data.