Data Access and Regulation

The course programme of the Prof. Orofino modules is detailed above:
1. Introduction
2. The fundamental right to personal data protection (I part)
3. The fundamental right to personal data protection (II part)
4. The European concept of data protection between EU and ECHR
5. Data protection terminology
6. Territorial and material scope;
7. General Principles of European Data Protection Law
8. The Legal Conditions relating to processing of personal data;
9. The rights of the data subject (I part)
10. The rights of the data subject (II part)
11. The obligations of the controller and of the processor (I part)
12. The obligations of the controller and of the processor (II part)
13. The DPO
14. The Member States' Independent Supervisory Authorities
15. The European Data Protection Board; Competence, tasks and powers
16. Transfers of personal data to third countries (non-EU countries)
17. Specific Type of Data (I part)
18. Specific Type of Data (II part)
19. Remedies and penalties
20. IA and Data protection

The programm of the third module (R. Fahley)
The course will begin with a discussion of the challenges presented to social science researchers by Big Data and the increasingly rigorous demands for transparency and open sharing of research data, and outline the considerations which researchers need to keep in mind when designing a data management plan for their project. Next we will introduce a variety of different data management tools, including flat files, local databases, and large-scale cloud storage systems. For each of these we will discuss strengths and weaknesses, and the kinds of data or analysis for which they might be suitable, and students will have an opportunity to try working with them (adding, manipulating and exporting data) in lab sessions, where they will learn the basics of the data specification and query syntaxes (SQL and NoSQL) that are commonly used for these systems. Finally, we will discuss best practices for creating a data management plan that will address considerations such as collaborating with other researchers, ensuring that your valuable data is securely backed up, and allowing you to easily share it publicly when your research is published. The course will conclude with a project in which students will design a data management plan for a hypothetical research project and write a short report justifying the choices they made.

Fourth module (Andrea de Angelis)
Fourth module (Andrea de Angelis)
The course is structured in three blocks: 1) an introductory block covering the essential knowledge for working with web data (notions of R programming, developing reproducible code, reporting in automated notebooks, version control, and Git/GitHub) and the main available secondary data sources. 2) A core block focusing on web data technologies (regexprs, HTML, CSS, XPath, XML, JSON). 3) An advanced block introducing the basics of API interaction (HTTP protocol, GET and POST methods, RESTful web APIs' workflow).