Open data: How to Use
Objectives
The main objective of the course is to offer a practical introduction to the automated collection and organisation of open data, while exploring some theoretical and ethical questions about open access.
The theoretical component will have as objectives:
- Introducing students to the issue of open data, in particular with regard to government data and science;
- Present and discuss the limits of open data and its ethical implications.
- Present the principles of open data distribution.
- The practical component will have as its objectives:
- Introduce students to the R programming language, an open access software widely used for automated data collection,
- management and analysis.
- Develop data management, manipulation and transformation capacity with R.
- Develop the ability to automatically extract data from digital sources with R.
General characterization
Code
02104625
Credits
10.0
Responsible teacher
Available soon
Hours
Weekly - 4
Total - 280
Teaching language
Portuguese
Prerequisites
Available soon
Bibliography
Kitchin, Rob (2014) The Data Revolution: Big Data, Open Data, Data Infrastructures and their consequences, SAGE Publications: Los Angeles.
Grolemund, Garret (2014) Hands-On Programming with R, O'Reilly Media: Cambridge.
Chang, Winston (2013) R Graphics Cookbook, O'Reilly Media: Cambridge.
Teaching method
This course will combine theoretical (30%) and practical (70%) lessons, the latter being held so that each student has access to a computer.
Evaluation method
Método de Avaliação - Final report (60%), Weekly exercises (40%)
Subject matter
1. Open data and contemporary society:
1.1. Definition and introduction to open data;
1.2. Open government data;
1.3. Open data and science.
2. Introduction to programming with R:
2.1.Object-oriented language;
2.2. Basic operations.
3. Data management with R:
3.1. Database management;
3.2. Data transformation;
3.3 Graphical data analysis.
4. Automated data extraction:
4.1. Extraction from digital sources;
4.2. Extraction from website;
4.3. Extraction of social networks.
5. Open access data availability.
Programs
Programs where the course is taught: