Visualização de Dados

Caracterização geral

Pré-requisitos

• Introdução à visualização
• Abstração de dados e tipos de dados
• Marcas e canais
• Visualização de tabelas
• Dados espaciais
• Gráficos
• Redes e árvores
• Cor
• Narrativa

Bibliografia

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.

Método de ensino

1st phase

• Data Visualization academic paper presentation - groups of up to 4 students (15%). The paper must be selected from one of the following journals:
• http://journals.sagepub.com/home/ivi
• https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945
• https://www.journals.elsevier.com/visual-informatics/

Papers from other journals can also be selected. In any case, the paper selection must be approved by the professor by email before 2/December. The list with the 5-minute presentations will be made available until 4/December

• Project report and presentation (35%). The dates of the presentations are 21 and 22 of January.
• 1^st phase exam (50%) (40 multiple choice and T or F questions, no minimum grade)

 2nd phase

• Project report and presentation (50%). It is not possible to improve the grade of the project presented on 21and 22 of January 2020.
• 2^nd phase Exam (50%) (minimum grade is 9.5 points, 3 open questions and 40 multiple choice and T or F questions).

Método de avaliação

Inglês.

Conteúdo

Aulas teórico-práticas relacionadas com conceitos de Visualização de Dados e software específico (Python).

Cursos

Cursos onde a unidade curricular é leccionada: