This course provides an introduction to information visualization. Students will learn the principles to design a visualization applicaiton, and they will experience advanced programming tools to develop such applications in practice. The course consists of both theoretical lectures in class and practical experiences both in class and through autonomous work of students
- Aims and content
- LEARNING OUTCOMES
Students will be provided with a sound grounding on the principles, methods, and techniques for effective visual analysis of data. Students will explore many aspects of visualization, including techniques for both spatial (e.g., gridded data from simulations and scanning devices) and non-spatial data (e.g., graphs, text, high-dimensional tabular data).Students will get acquainted with the principles from computer graphics and human perception, and will learn visualization techniques and methods for a broad range of data types, specifically scientific visualization techniques for spatial data, and information visualization techniques for abstract data. Students will be involved in project activities.
- Visual perception
- Data abstraction
- Marks and channels
- Task abstraction
- Visualization of table data
- Visualization of geographic data
- Manipulazion of views
- Multiple views
- Data reduction
- Technical tools: D3, Tableau
- RECOMMENDED READING/BIBLIOGRAPHY
Tamara Munzner.VisualizationAnalysis and Design.AK PetersVisualization Series. CRC Press, 2014
Scott Murray. Interactive Data Visualization for the Web. O’Reilly, 2013
- Exam Board
90529 - DATA VISUALIZATION
Enrico Puppo (President)
- TEACHING METHODS
This course uses the method of flipped classroom: students are expected to read course material before it is presented in class.
- Class lectures for:
- Theory (design principles)
- Programming techniques
- Analysis of code
- In class exercises resolved by students
Class attendance is registered and evaluated in final mark.
- Class lectures for:
- EXAM DESCRIPTION
- 3-5 small homeworks during class period (20% of final mark + bonus for optional parts)
- FInal project (50% of final mark + bonus for optional parts)
- Oral exam (30% of inal mark)
Oral exam must be taken after delivering the final project. If the student has atteded over 80% of classes, it consists just of a discussion of the project itself, in relation to the theory presented in class; if the student has attended between 50% and 80% of classes, it may also include some questions related to the theory presented in class; if the student has attended less than 50% of classes, it will consist mainly of questions concerning the whole syllabus.
- LESSONS START
- OFFICE HOURS FOR STUDENTS
Appointment by email to email@example.com
During class period appointments for groups can be set by posting on the course forum on AulaWeb.
Date Time Type Place Notes 16 febbraio 2018 9:00 Esame su appuntamento Genova 27 luglio 2018 9:00 Esame su appuntamento Genova 21 settembre 2018 9:00 Esame su appuntamento Genova 28 febbraio 2019 9:00 Esame su appuntamento Genova