2026
Fundamentals of Data Visualization
Name: Fundamentals of Data Visualization
Code: DES14267M
6 ECTS
Duration: 15 weeks/156 hours
Scientific Area:
Human Kinetics
Teaching languages: Portuguese
Languages of tutoring support: Portuguese
Presentation
n.a.
Sustainable Development Goals
Learning Goals
At the end of the course, students should:
1. Know the fundamental principles, methods, and concepts required to visualize data for publications, reports, or presentations.
2. Have a practical sense for why some graphs and figures work well, while others may fail to inform or actively mislead:
3. Know how to create a wide range of plots in R (a widely used, and freely available programming language for data analysis) using ggplot2 and in open-source platforms;
4. Know how to refine plots for effective presentation.
1. Know the fundamental principles, methods, and concepts required to visualize data for publications, reports, or presentations.
2. Have a practical sense for why some graphs and figures work well, while others may fail to inform or actively mislead:
3. Know how to create a wide range of plots in R (a widely used, and freely available programming language for data analysis) using ggplot2 and in open-source platforms;
4. Know how to refine plots for effective presentation.
Contents
1. Aesthetics and types of data;
2. Color scales;
3. Visualizing amounts and distributions:
3.1. Bar plots;
3.2. Histograms and density plots;
3.3. Proportion plots;
3.4. Visualizing associations among two or more quantitative variables:
4. Scatter plots and correlograms;
4.1. Dimension Reduction;
5. Visualizing rime series and trends;
6. Visualizing of estimation statistics;
7. Data visualization layout;
8. Data visualization softwares.
2. Color scales;
3. Visualizing amounts and distributions:
3.1. Bar plots;
3.2. Histograms and density plots;
3.3. Proportion plots;
3.4. Visualizing associations among two or more quantitative variables:
4. Scatter plots and correlograms;
4.1. Dimension Reduction;
5. Visualizing rime series and trends;
6. Visualizing of estimation statistics;
7. Data visualization layout;
8. Data visualization softwares.
Teaching Methods
Exposure matter orally with the help of audio-visual means and calculation programs. Student-centered learning, as a facilitator of learning through research and reading articles and documents, promoting true understanding, valuing and promoting cooperative and collaborative work between the group members.
Theoretical-practical complementarity guarantees the deepening of the students' capacities, as is the objective of the course. Its organization will equip students with a theoretical foundation and technical skills to use R programming and open access platforms to transform data into visual information. The use of libraries with advanced functionality for data visualization will be the basis of a practical component.
The evaluation will include the development and presentation of an individual technical report related to the visualization of a database (related to sport or health) made available to students: (i) final document (75%); (ii) presentation of the final document (25%).
Theoretical-practical complementarity guarantees the deepening of the students' capacities, as is the objective of the course. Its organization will equip students with a theoretical foundation and technical skills to use R programming and open access platforms to transform data into visual information. The use of libraries with advanced functionality for data visualization will be the basis of a practical component.
The evaluation will include the development and presentation of an individual technical report related to the visualization of a database (related to sport or health) made available to students: (i) final document (75%); (ii) presentation of the final document (25%).
Accreditations and Certifications
