Content
The topics covered in this course include:
- Background on open data;
- Benefits and risks of opening data;
- Models related to using and publishing open data.
Syllabus
Learning Objectives
This course introduces the foundational principles of Open Data, equipping undergraduate students in Information Science with the knowledge and skills to find, analyse, and effectively reuse open datasets. Through a combination of lectures, practical activities, and assignments, students will explore the benefits and challenges of Open Data and develop a deeper understanding of its potential applications and implications. It is designed with the following objectives:
- To gain an understanding of Open Data, its essential aspects, and the principles of opening data;
- to learn how to find, analyse, and reuse open datasets;
- to learn the processes involved in preparing and publishing open datasets.
These objectives provide the foundation for the course and guide the learning outcomes.
Methods
The course employs the following methods to support learning:
- Course presentations;
- Exploration of online services;
- Hands-on exercises;
- Engagement with scholarly literature.
These methods are intended to foster both theoretical understanding and practical application of the course material.
Course Outline (2025-2026)
An exam (contrôle continu) will be held at the end of the fourth and final session. It will consist of multiple-choice and open-ended questions, will last a maximum of one hour, and will be conducted through Cyberlearn. All course notes and access to the internet are permitted. However, the use of Large Language Models (LLMs) and communication tools is prohibited.
WarningMissed Examination Policy
If a student is absent during the last session and misses the examination for legitimate reasons, a substitute assignment will be organised by the tutor.