1052057: Visual Analytics

This is the official page of Visual Analytics Course 2020-2021 (Fall 2020)
Teacher: Prof. Giuseppe Santucci
TA: Dr. Marco Angelini
TA: Ing. Simone Lenti

Lecture hours and rooms

Tuesday 11:00 - 13:00 room A4 (first lecture on October 6th)
Thursday 10:00 - 13:00 room A5

Virtual room :
Join Zoom Meeting
https://zoom.us/j/94672176688?pwd=clZkVFZVMVFTcUFoaFptOTdhNDBjUT09

Meeting ID: 946 7217 6688
Passcode: VAclass

The course encompasses 3 main modules:

Number visualization
Visualizing quantitative information requires understanding the different kinds of numbers, the basic table and graph formats and to avoid common errors and lies. This module will present a comprehensive survey of existing solutions, focusing on how to present quantitative information clearly and effectively.

Topics:
Introduction
Common errors & lies
Kinds of number
Table and graphs


Information Visualization
The main goal of information visualization is to reveal the structure, extract meaning, and navigate large and abstract data sets (vs. scientific data visualization, cartography, and computer graphics, not addressed in this course), using interactive computer-based representations that utilize the powerful processing capabilities of the human eyes. The increasing interest in information visualization has led to the development of many interesting and effective ideas about how to visualize abstract information. This module will present a comprehensive survey of existing approaches, focusing on how to present information clearly and effectively.

Topics:
Introduction
Representation
-Encoding
-Type of data – Univariate / Multivariate data
-Data and relationships
-Perceptual issues
Presentation
-Space limitation
-Time limitation
Interaction
-Continuous interaction
-Stepped interaction
Case studies
d3.js

Visual Analytics
"Visual Analytics is the science of analytical reasoning facilitated by visual interfaces.”
Visual analytics techniques are needed to integrate data from massive, dynamic, ambiguous, and often conflicting sources, analyze the data to derive new insights, make critical decisions in real-time.
This module will present the main ideas underlying Visual analytics, focusing on data transformation, complex data presentation and data, algorithms, and visualization interaction.

Topics:
Introduction
- applications, tools, research challenges
Representation and Transformation
- data wrangling
- dimensionality reduction
- data reduction/summarization/modeling
Presentation and Interaction
- visualization techniques/scalability
- space-time
- visual data mining
- interaction technique