Skip to main content
CODE 90529
ACADEMIC YEAR 2023/2024
CREDITS
SCIENTIFIC DISCIPLINARY SECTOR INF/01
LANGUAGE English
TEACHING LOCATION
  • GENOVA
SEMESTER 1° Semester
TEACHING MATERIALS AULAWEB

OVERVIEW

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

Learning principles, methods, and techniques for effective visual analysis of data, including techniques for visualizing both spatial and non-spatial data, principles from computer graphics and human perception.

PREREQUISITES

Basics of web development (HTML, CSS, JavaScript)
Basic notions of statistics 

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 are for intrudicing theory and design principles. 
Practice consists in simple data visualization tasks implemented individually by students
Homework will be assigned. 
Class attendance may affect the final assessment.

SYLLABUS/CONTENT

This course will make use of elementary client-side web programming; students are expected to have some backgound on HTML5, CSS, and Javascript. 

 

 

Visual perception

Data abstraction

Marks and channels

Task abstraction

Visualization of categorical data

Visualization of temporal data

        Visualization of correlations

Visualization of geographic data

Technical tools: D3.j

RECOMMENDED READING/BIBLIOGRAPHY

Scott Murray. Interactive Data Visualization for the Web. O’Reilly, 2013 

Jonathan Schwabish. Better Data Visualizations. Columbia University Press, 2021

Koponen, Juuso, and Jonatan Hildén. Data visualization handbook. Aalto korkeakoulusäätiö, 2019.

Tamara Munzner.VisualizationAnalysis and Design.AK PetersVisualization Series. CRC Press, 2014 

Amelia Wattemberger. Fullstack D3 and Data Visualization: Build beautiful data visualizations with D3

TEACHERS AND EXAM BOARD

Exam Board

ANNALISA BARLA (President)

CLAUDIO MANCINELLI

ENRICO PUPPO (President Substitute)

LESSONS

LESSONS START

In agreement with the calendar approved by the Degree Program Board of Computer Science.

Class schedule

L'orario di tutti gli insegnamenti è consultabile all'indirizzo EasyAcademy.

EXAMS

EXAM DESCRIPTION

Attendance
Quiz during class - Class attendance

Homework [20%]
About four assigned along the course - small effort, strict deadlines

Project [50%]
Assigned during the course - big work, completed by the end of the course

Oral [30%]
After submitting the project
By appointment for groups of students
Depth of oral exam proportional to attendance.

The score of quizzes+homework will guide the selection of the topics during the oral exam

Exam schedule

Data Ora Luogo Degree type Note
15/01/2024 09:00 GENOVA Scritto + Orale
29/01/2024 09:00 GENOVA Scritto + Orale
12/02/2024 09:00 GENOVA Scritto + Orale
10/06/2024 09:00 GENOVA Scritto + Orale
08/07/2024 09:00 GENOVA Scritto + Orale
09/09/2024 09:00 GENOVA Scritto + Orale