The course provides an overview of the main theories, concepts, principles, techniques, heuristics and tools for the design, development and evaluation of interactive data graphics.

The student will acquire the knowledge and skills related to:

Objective 1 (O1) – knowledge of theory and principles:
1) Theories of perception, cognitive biases, notions of semiotics and pragmatics;
2) Data types and physical signals (pre-attentive selection, color theory, gestalt theory, and the like);

Objective 2 (O2) – knowledge of basic concepts and models
3) The grammar of data graphics and its application to encoding and decoding of visual information;
4) Classifications and taxonomies of data graphics;
5) Main design principles;
6) Models and heuristics for a proper interaction design of visual interfaces;

Objective 3 (O3) – Practice, applications and evaluation of concepts and models:
7) Tools and resources for the advanced design of data graphics, static and interactive infographics, and dashboards (Python libraries and Tableau);
8) Main techniques for choosing and applying the best qualitative and quantitative evaluation test to data graphics and interactive dashboards;
9) Notions of visual information literacy and statistical techniques for its evaluation;

Objective 4 (O4) – Soft skills
10) Communication skills related to the acquisition and application of the visual language of data;
11) Evaluation skills related to the quality assessment of visual artifacts and tools.