Credits: 4 ECTS
Electives in advanced research methods and techniques
“Data Visualization for International Relations” is oriented towards giving tools to the student for the basic representation of data typically employed in international relations. It is offered at the end of the Master with the purpose of enabling the student to use those tools for the Master thesis. Nevertheless, the competences achieved can —and must— be useful for future professional development.
Data visualization is often neglected in data analysis, although it is indeed a central pilar in understanding trends, processes, streams of data, relationships between any given unit of analysis or simply to suggest potential patterns. Moreover, data visualization is usually considered as a pre-supposed skill when in fact it requires not only substantial knowledge about the topics, but also methodological understanding and creative thinking and artistic competencies.
The course is emminently practical and guides the student from the most basic procedures of data management, in order to be able to deal with high quantities of data, towards complex visual representations of data such as maps, interactive plots, and videos. It employs the R programming language, offering at the same time a gentle introduction to the tool. R is considered the lingua franca of statistics and data analysis nowadays, and offers a comprehensive set of tools for data visualization, including lots of practical documentation and examples.
The course is structured in 6 sessions of 4 hours (3, 4, 5, 9, 10 and 11 of June), with a nonpresential exercise before the course.
The sessions will combine both traditional lecture-style teaching along with time to work alone on the personal projects to be supervised by the instructor. Students must bring their laptops to solve on their own problems and challenges to be answered in class.
In some sessions the student may be asked to apply to their own data a required reading.
At the end of the sessions the student will have to explain which aspects of the session can be applied to the master thesis and the final exercise of the course. There is the possibility to ask the teacher to provide exercises in order to prepare future sessions. Although they will not be evaluated, the student will get feedback.
Grading will be based on a final report (60% of the final grade) in which the student will show that the competences have been achieved and two intermediate progress reports (20% each one).
The topic of the final report will be negotiated between the teacher and the student. However, students that are in an appropriate stage in their Master thesis preparation may decide to incorporate data presentation into the final exercise that is relevant and useful to the completion of the dissertation.
The final report will have to contain the practical application of at least 2 techniques of data visualization covered during the course. Special attention will be given to the fit of the visualizations used with the objective of the analysis, the development and justification of its use, and the ability to communicate the results.
The delivery of the final report will be up to a week after the last session of the course, in digital version in a single compressed file the email address of the teacher, containing a report (in PDF), the dataset used, the code commented and explained, and other electronic objects with the visualizations (video, webpages, images).
The two intermediate progress reports will be delivered at approximately 1/3 of the course and 2/3 of the course, with a self-evaluation of the progress and an expected plannification of the rest of the work to be performed.