Questa è una vecchia versione del documento!
To keep updated with the last news of the course, subscribe at the Telegram channel: https://t.me/va602aa
Students will be admitted to the exam after the registration on the website http://esami.unipi.it. The exam consist of a discussion of the project. It is mandatory to submit a short report (6-10 pages) within the deadline by mail to instructor, specifying the tag “[VA]” in the subject.
The student may choose one of the following project proposals. She/he can also propose an additional topic. In this case a project proposal should be submitted for approval, containing a description of the data, a sketch of the possible visualization and the motivation for the project.
The project assignment for the exam consist in the realisation of a web application addressing data and mini challenges presented for the VAST challenge XXXX (http://www.vacommunity.org/VAST+Challenge+XXXX). The general contest of the challenge asks to analyse and explain the possible causes of pollutants spreading in a natural park, threatening the survival of a bird species in the park.
This is a project that requires to implement a module with visual interface to explore and manage the project Didactic Data Mining developed within the course of Data Mining. The module is implemented in Python and provides a RESTful interface to create an experiment, to insert a dataset and to follow the evolution of a data mining algorithm on the dataset.
This is a project that requires to extend the visual interface of the NDLib - Network Diffusion Library developed within the KDDLab. The core library is implemented in Python and provides a RESTful interface to create an experiment, to insert a network and to execute a diffusion simulation over the network.
All exercizes and code discussed during each lesson are available as a Git repository at: https://github.com/rinziv/VA2017
|1.||19.02.2018 14:00-16:00||N1||Intro: Visual Analytics Process;||Slides ; VisMaster Book (Chapter 2)|
|23.02.2018 14:00-16:00||–||No lesson today|
|2.||26.02.2018 14:00-16:00||N1||Intro: Visual Analytics Process;||Slides|
|3.||02.03.2018 14:00-16:00||C1||Development Environment setup: Node.js, NPM, GIT||Slides|
|4.||06.03.2018 11:00-13:00||N1||Visual Variables||Slides|
|09.03.2018 14:00-16:00||–||No lesson today|
|6.||13.03.2018 11:00-13:00||L1||Introduction to SVG||Slides|
|16.03.2018 14:00-16:00||–||No lesson today|
|7.||19.03.2018 14:00-16:00||N1||Introduction to D3.js|| Slides
GitHub - First project
|8.||23.03.2018 14:00-16:00||C1||Do and Donts. Examples and case studies||Slides|
|9.||26.03.2018 14:00-16:00||N1||First examples with D3||GitHub Lines|
|Spring break||No lessons - Assignment: implement lines project with other shapes|
|10.||12.04.2018 14:00-16:00||O||Project assignement; Color Models||Slides|
|11.||17.04.2018 16:00-18:00||L1||Project assignement; Scales||Slides|
|12.||20.04.2018 14:00-16:00||C1||Scales and Reusable Chart Components|| Slides
Resusable Charts in D3
|13.||23.04.2018 14:00-16:00||L1||Data Handling - Crossfilter||Slides|
|14.||27.04.2018 14:00-16:00||C1||Data Handling - Express and DBMS||see Lesson 13|
All source code of exercises are available at the URL: https://github.com/VA602AA-master