This course will teach how to create visualizations that effectively communicate the meaning behind data through visual perception. Concepts about human perception of graphic information as well as different ways of mapping different forms of quantitative and qualitative data will be addressed. We will use R software to complete data visualization exercises aiming to explore visual interaction with data for analysis and communication. Demonstrations with Excel/Tableau Public will also be used to teach data visualization concepts.
- Describe how computer graphics are used to visualize data.
- Understand how users process information through visual displays.
- Understand the impact of colors on perception.
- Know different techniques for visualizing different forms of data.
- To be aware of current research in Data Visualization.
- Use R toolkit with packages such as ggplot2 and ggmap to compute and generate statistics and visualizations.
- Share interactive visualizations using Shiny Apps.
- Being able to tell stories with data.
Pedro da Costa Brito Cabral
Weekly - Available soon
Total - Available soon
Portuguese. If there are Erasmus students, classes will be taught in English
Tamara Munzner (2014). Visualization Analysis and Design. CRC Press.
Nathan Yau (2011). Visualize this ¿ The FlowingData Guide to Design, Visualization, and Statistics. Wiley Publishing, Inc.
Theoretical-practical classes related with Data Visualization concepts and specific software (Excel, R, Tableau Public).
- Data Visualization academic paper presentation - groups of up to 4 students (15%). Individual presentations are not allowed because the idea is to promote discussion and team work. The paper must be selected from one of the following journals:
Papers from other journals can also be selected. In any case, the paper selection must be approved by the professor by email before 19/March. The list with the 5-minute presentations will be made available until 22/March
- Project report and presentation (35%). The dates of the presentations are 11 and 12 of June after 18:30h. Dates will be arranged individually.
- Test during the class (50%) (40 multiple choice and T or F questions, no minimum grade). There is not 1st phase exam.
- Project report and presentation (50%). It is not possible to improve the grade of the project.
- 2nd phase Exam (50%) (minimum grade is 9.5 points, 3 open questions and 40 multiple choice and T or F questions).
1. Introduction to visualization
2. Data Abstraction and data types
3. Marks and channels
4. Evaluation. Rules of Thumb.
5. Visualizing Tables.
6. Spatial Data.
7. Graphs. Networks and Trees.
9. Reduce items and attributes