Scientific visualization

A.Y. 2020/2021
6
Max ECTS
48
Overall hours
SSD
INF/01
Language
Italian
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
Course syllabus and organization

Single session

Responsible
Lesson period
Second semester
Lectures will be online
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.
Concepts of Dashboard design: how to integrate and merge all the explained visualization charts and visualization tricks to produce an informative dashboard
Techniques for dashboard design.
Visual data analysis: classic techniques and state of the art techniques.
Critical Analysis of state-of-the-art works introducing visualization techniques in scientific fields.
Open Data
Graph Visualization
Neural Network Visualization

Labs: data visualization examples (based on real problems) with MATLAB (and eventually R - package ggplot2)
Prerequisites for admission
None
Teaching methods
Lectures + laboratories
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
Assessment methods and Criteria
spoken enquiry + project
INF/01 - INFORMATICS - University credits: 6
Lessons: 48 hours
Professor: Casiraghi Elena
Professor(s)
Reception:
https://zoom.us/j/8134547215