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.
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.
This course uses the method of flipped classroom: students are expected to read course material before it is presented in class.
Class attendance is registered and may affect the final assessment.
This course will make use of elementary client-side web programming; students are expected to have some backgound on HTML5, CSS, and Javascript. Students that wish to take this course but do not know about these topics may easily back up through Topics in Computer Science.
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
Ricevimento: Appointment by email
ANNALISA BARLA (President)
CLAUDIO MANCINELLI
ENRICO PUPPO (President Substitute)
First semester
Attendance Quiz during class - Class attendance [remote participation counts] 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.
