The main objectives are to give students the necessary bases to understand the impact of visual representations in the analysis and understanding of complex data, to give them the theoretical foundations necessary to create effective visualizations (the principles of perception and semiotics, etc.) and bring them up to date with state of the art in data visualization. It is also intended that students get to know the history of visualization and notable visualizations. At the end of the semester the student should: understand the main visualization techniques and the theoretical foundations necessary for their creation; being able to critically evaluate visualizations, understanding their strengths and weaknesses, and being able to suggest improvements and improvements; be able to understand the data and determine what problem is trying to solve; having the ability to read and discuss current literature; and being able to conceptualize ideas and interaction techniques through sketches.
Weekly - 2
Total - 140
- Brewer, Cynthia A. "Color use guidelines for data representation." In Proceedings of the Section on Statistical Graphics, American Statistical Association, pp. 55-60. 1999;
- Cawthon, Nick, and Andrew Vande Moere. "The effect of aesthetic on the usability of data visualization." In Information Visualization, 2007. IV'07. 11th International Conference, pp. 637-648. IEEE, 2007;
- Chen, Chaomei. "Top 10 unsolved information visualization problems." IEEE computer graphics and applications 25, no. 4 (2005): 12-16;
- Gershon, Nahum, and Ward Page. "What storytelling can do for information visualization." Communications of the ACM 44, no. 8 (2001): 31-37;
- Segel, Edward, and Jeffrey Heer. "Narrative visualization: Telling stories with data." IEEE transactions on visualization and computer graphics 16, no. 6 (2010): 1139-1148;
- Tufte, Edward R. "The visual display of quantitative information." Vol. 2, no. 9. Cheshire, CT: Graphics press, 1983.
Students will receive exposure focused on the topic of information visualization, in order to develop critical thinking on the key issues of this theme. They will also be exposed to practical development and will have contact with some tools to support the creation of visualization. Classes will have a theoretical / practical character.
The first half of each class is predominantly theoretical, with the material presented, illustrated with examples.
The second half of the class is dedicated to the discussion of mandatory readings, the main course work (individual and group) and to carry out small practical tasks on the subject presented in the first half of the class.
Report of a seminar or field trip(40%), Attendance and Participation(20%), Project(40%)
- Telling visual stories with data;
- Visualization history;
- The role of data mining and open data;
- Wisdom, Data, Information, and Knowledge;
- Exploratory versus explanatory;
- Directed by the author versus directed by the reader;
- The specifics of narrative visualization;
- The value of visualization;
- The data and why to visualize;
- Visualization in other study areas;
- The design of the visualization;
- The process;
- Types (sets and sequences, temporal data, maps, shapes, text and hypertext, hierarchies and graphics);
- Nominal, ordinal, interval and proportion;
- Density, focus and small multiples;
- Environment | Desktop, Mobile, Tablet and more;
- How did narratives evolve on different platforms?;
- Conventional and unconventional forms of presentation;
- Success stories: who is innovating in this space?;
- Perception, aesthetics, interactivity, animation, color, narrative and software.
Programs where the course is taught: