Scientific Visualization
A.Y. 2019/2020
Learning objectives
The course has two main purposes. The first purpose is to introduce the main data visualization techniques, which, when properly used, can allow both the visual analysis of the data, in order to discover the relevant information and relationships they express, and the effective dissemination of the obtained results. For each type of chart, its main features, functionalities and (appropriate) uses will be presented. The second purpose of the course is to provide the basic concepts for the design of "information dashboards"; they are (interactive) applications allowing a (in real time) monitoring of a system, through the (interactive and real-time) visualization of a set of system performance metrics.
Expected learning outcomes
After the course the student must be able to choose the proper graph depending on the data to be analyzed or displayed. He must be capable of designing a visually informative information dashboard for system performace assessment
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
Information Visualization and Data Visualization: similarities and differences.
Visualization and Perception.
Color and Color Perception.
Plots and graphs for data visualization e for dataset comparison: main components, characteristics, usage, advantages and drawbacks.
Infographics: descriptions and main characteristics.
Information Dashboards: description and main components.
Techniques for dashboard design.
Visual data analysis: classic techniques and state of the art techniques.
Critical Analysis of state-of-the-art works introduzing visualization techniques in scientific fields.
Visualization and Perception.
Color and Color Perception.
Plots and graphs for data visualization e for dataset comparison: main components, characteristics, usage, advantages and drawbacks.
Infographics: descriptions and main characteristics.
Information Dashboards: description and main components.
Techniques for dashboard design.
Visual data analysis: classic techniques and state of the art techniques.
Critical Analysis of state-of-the-art works introduzing visualization techniques in scientific fields.
Prerequisites for admission
Basic math.
English language.
No specific course must be followed in advance.
English language.
No specific course must be followed in advance.
Teaching methods
lectures, seminars from experts in the field, state-of-the-art paper presentation, exercises.
Teaching Resources
ppt Slides from each lecture (to be downloaded from: http://ecasiraghivs.ariel.ctu.unimi.it/v5/home/Default.aspx).
state-of-the-art papers read during the course (to be downloaded from: http://ecasiraghivs.ariel.ctu.unimi.it/v5/home/Default.aspx).
Books:
Stephen Few: "Now you see it"
Stephen Few: "Dashboard design"
Stephen Few: "Show me the numbers"
Articles from the state of the art
state-of-the-art papers read during the course (to be downloaded from: http://ecasiraghivs.ariel.ctu.unimi.it/v5/home/Default.aspx).
Books:
Stephen Few: "Now you see it"
Stephen Few: "Dashboard design"
Stephen Few: "Show me the numbers"
Articles from the state of the art
Assessment methods and Criteria
Exercises during the lessons and final project, which will be evaluated through presentation to other students.
Grades: 15 (not sufficient), 18-30 cum Laude (positive evaluations).
Grades: 15 (not sufficient), 18-30 cum Laude (positive evaluations).
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor:
Casiraghi Elena
Shifts:
-
Professor:
Casiraghi ElenaProfessor(s)