Studying at the University of Verona
Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.
Study Plan
The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.
1° Year
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2° Year It will be activated in the A.Y. 2026/2027
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| Modules | Credits | TAF | SSD |
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1 module among the following2 modules among the following1 module among the following
A.A. 2025/26 e 2026/27 - Network science and econophysics not activated
A.A. 2026/27 Complex systems and social physics not activated1 module among the following2 modules among the followingLegend | Type of training activity (TTA)
TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.
Data visualisation (2025/2026)
Teaching code
4S009065
Teacher
Credits
6
Language
English
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
Period
1st semester dal Oct 1, 2025 al Jan 30, 2026.
Courses Single
Authorized
Learning objectives
The course aims to provide students with an introduction to the main problems of data visualization. An overview of the critical aspects of visualization related to graphic design, perceptual psychology, cognitive sciences will be provided, and practical tools will be provided for the realization of effective visualizations (on the web) At the end of the course the student has to show to have acquired the following skills:
- understanding of the design issues of effective data visualizations
- understanding of the common data-visualization techniques for each type of data and application domain (multivariate data, networks, texts, cartography, etc.) with their features and limitations
- ability to read and discuss research papers from the data visualization literature
- ability to choose the most suitable visualization techniques for each type of data and application task
- ability to create interactive visualizations in the browser using HTM5 and Javascript
Prerequisites and basic notions
Data structures and Python programming basics
Program
- Introduction to data visualization: motivation, visualization problems, tasks and goals
- Design evaluation
- Color and perception and mapping of data on a color scale
- Marks and channels
- Guidelines for visualization design, ethics in visualization
- Data, models and data encoding, filtering, aggregation, multidimensional data
- Graphs and their visualization
- Tabular data visualization, graph and network visualization
- Maps, scientific visualization, image and volume visualization
- Spatial layout management, view manipulation, focus and context
- Interaction, user interface elements, animation, dashboards, multiple visualizations
- Prototyping using visualization packages in python
Bibliography
Didactic methods
Lectures and guided examples in Python
Learning assessment procedures
Written exam and evaluation of practical assignments. The written exam consists of 4 open questions on the theory program. The assignments will consist of exercises on the practical part to be delivered.
Evaluation criteria
Students will have to demonstrate understanding of the design issues of a visualization application, be aware of the main types of data and encodings, the issues of visual mapping and the related human factors, the main visualization techniques used for the various types of data. Students will have to be able to demonstrate the practical ability to design effective data visualizations using basic libraries and following the rules and principles of design.
Exam language
Inglese/English
