Information Visualization

Recommended Prerequisites

Average knowledge of programming, multimedia and design.   

Teaching Methods

The unit includes theoretical lectures where the fundamental concepts, principles and techniques and there are presented and explained in detail.

Lectures of practical nature play the role of strengthening the connection between theoretic knowledge and its practical application. To pursue this goal we focus on problem solving and on the analysis of case studies that require combining different theoretical concepts and that promote critical reasoning. 

Learning Outcomes

This course adopts an encompassing perspective, understanding information visualization as a form of cognitive augmentation. It focuses on computational approaches to information visualization, presenting the theoretical foundations to build effective visualizations, providing a set of classical techniques for each type of visualization structure and promoting the application of hybrid techniques or the creation of new ones. The theoretical foundations and technical knowledge should be applied to real data scenarios, mainly investing in interactive visualizations, visual analytics and modern approaches to visualization discussed during this course.

The main competencies to be developed are:

Instrumental – analysis and synthesis, problem solving

Personal – critical thinking

Systemic - practical application of the theoretical knowledge; research

The secondary competences are:

Instrumental – organizing and planning

Personal – work in teamsSystemic – autonomous learning, creativity.

Work Placement(s)

No

Syllabus

The purpose of visualization

History of visualization

Descriptive statistics

Graphic semiology

Perception and cognition for visualization:

     graphical integrity;

     color in visualization;

     small multiples;

     layering;

     clustering.

Structures and visualization models:

     hierarchical structures: trees;

     relational structures: networks;

     temporal structures: timelines and flows;

     spatial structures: maps;

     spatio-temporal structures;

     textual structures.

Approaches to visualization: between reasoning and communication:

      visual analytics;

      figurative visualization and storytelling

New topics in visualization:

      web based visualization;

      visualization for the social web;

      participatory visualization;

      visualization for big data.

Assessment Methods

Assessment
Resolution Problems: 20.0%
Project: 80.0%

Bibliography

E. R. Tufte, Beautiful evidence. Graphics Press, 2006

E. R. Tufte, The Visual Display of Quantitative Information, 2nd ed. Connecticut:, 2007

M. Friendly, “A Brief History of Data Visualization,” in Springer Handbooks Comp.Statistics, Springer Berlin Heidelberg, 2008, pp. 15–56

T. Finke and S. Manger, Informotion: Animated Infographics. Gestalten Verlag, 2012

I. Meirelles, Design for Information: An Introduction to the Histories, Theories, and Best Practices Behind Effective Information Visualizations. Rockport Publishers, 2013

M. Lima, Visual Complexity: Mapping Patterns of Information. Princeton Architectural Press, 2011

N. Yau, Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics. John Wiley & Sons, 2013

J. Bertin, Sémiologie graphique: Les diagrammes, les réseaux, les cartes. Paris: Mouton & Gauthier-Villars, 1967

E. Lupton and J. C. Phillips, Graphic Design The New Basics. Princeton Architectural Press, 2008

W. S. Cleveland, The elements of graphin.