DATA VISUALIZATION

DATA VISUALIZATION

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iten
Code
90529
ACADEMIC YEAR
2017/2018
CREDITS
6 credits during the 1st year of 9014 Computer Science (LM-18) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
INF/01
LANGUAGE
English
TEACHING LOCATION
GENOVA (Computer Science)
semester
2° Semester

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

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.

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 evaluated in final mark.

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
  • 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 

TEACHERS AND EXAM BOARD

Ricevimento: Appointment by email to enrico.puppo@unige.it During class period appointments for groups can be set by posting on the course forum on AulaWeb.

Exam Board

ENRICO PUPPO (President)

PAOLA MAGILLO

LESSONS

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 evaluated in final mark.

LESSONS START

Second semester

EXAMS

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.