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DATA VISUALIZATION

CODE 90529
ACADEMIC YEAR 2022/2023
CREDITS
  • 6 cfu during the 2nd year of 10852 COMPUTER SCIENCE (LM-18) - GENOVA
  • 6 cfu during the 1st year of 11160 COMPUTER ENGINEERING (LM-32) - GENOVA
  • 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.

    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
    • Homework

    Class attendance is registered and 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. Students that wish to take this course but do not know about these topics may easily back up through Topics in Computer Science. 

    • Visual perception
    • Data abstraction
    • Marks and channels
    • Task abstraction
    • Visualization of table data
    • Visualization of geographic data
    • Manipulation of views
    • Multiple views
    • Data reduction
    • Technical tools: D3

    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 

    TEACHERS AND EXAM BOARD

    Exam Board

    ANNALISA BARLA (President)

    CLAUDIO MANCINELLI

    ENRICO PUPPO (President Substitute)

    LESSONS

    LESSONS START

    First semester

    Class schedule

    All class schedules are posted on the EasyAcademy portal.

    EXAMS

    EXAM DESCRIPTION

    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.

    Exam schedule

    Date Time Location Type Notes
    14/06/2023 09:00 GENOVA Esame su appuntamento
    12/09/2023 09:00 GENOVA Esame su appuntamento