• Salvatore Rinzivillo (rinzivillo [at] isti [dot] cnr [dot] it)

• Monday, 14:00 - 16:00, Aula N1 Polo Fibonacci
• Friday, 14:00 - 16:00, Aula C1 Polo Fibonacci

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• [new] Updated the list of project proposals for the final exam
• The lesson planned on April 16, will be moved on April 17th 16-18, room L1
• The lesson planned on April 13, will be anticipated on April 12th 11-13, room O
• There will be class on March 16th
• There will be class on March 9th. We will have an extra lesson on March 13th, from 11 to 13 in Aula L1
• There will be class on March 5th and March 9. We will have an extra lesson on March 6th, from 11 to 13 in Aula N1
• A new edition is starting on Monday 19th February

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.

• A project should have the following requirements:
• The application should contain several visual widgets, each providing insights on a selection of dimensions of the original data
• It is possible to use state-of-the-art charts (bar charts, line charts, etc.) and libraries (plotly, nvd3, etc). It is a plus to implement a novel, original visualization to present the data in a creative, non-trivial way. (see examples on Vast Challenge 2008 developed in class)
• Interactivity should be implemented, providing toolbars, selections and filters for the data.
• The visual widget should interact among them, realising a set of linked display to browse the data across multiple dimensions
• The project should be submitted as a Git repository
• The project report should be submitted 4 days before the discussion and should discuss at least the following points:
  • Description of data and presentation of the pattern or model to communicate
  • design choices: colors, interactions, shapes, transformations)
  • state-of-art: similar tools or interfaces for the same problem
  • detailed description of the visualization with description of interaction
  • use case example for an analytical task

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 2017 (http://www.vacommunity.org/VAST+Challenge+2017). 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.

• It is possible to choose among Mini Challenge 1 and Mini Challenge 2: The first mini challenge regards the analysis of logs of traffic flows of vehicles within the park; the second mini challenge ask to analyse the data of emissions of industries and company in the neighbourhood of the park
• The project can be developed also in group (at most two students). For the groups, at least the two challenges should be addressed.
• The data can be downloaded from the website above

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.

• The students should select a data mining algorithm after a preliminary discussion with the project manager (Prof Monreale)
• The requirements of the project are discussed in this extended committe. The student is autonoums in developing and proposing the visual interface
• From a technical point of view, a few constrains are already set:
  • The project should be developed within the GitHub platform, accessing the repository of the main Project (it will be created a branch dedicated to the student)
  • The interfaces and data schema of the whole project are fixed and cannot be changed (any modification should be discussed)
  • The module developed by the student should conform the code quality rules already set (linting, testing, etc.)
  • The project uses the Vue.js framework for developing the application

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.

• The students should select one task to extent the interface, after a preliminary discussion with the project managers (Rossetti, Milli, Rinzivillo)
• The requirements of the project are discussed in this extended committe. The student is autonoums in developing and proposing the visual interface
• From a technical point of view, a few constrains are already set:
  • The project should be developed within the GitHub platform, accessing the repository of the main Project (it will be created a branch dedicated to the student)
  • The interfaces and data schema of the whole project are fixed and cannot be changed (any modification should be discussed)
  • The module developed by the student should conform the code quality rules already set (linting, testing, etc.)
  • The project uses the Vue.js framework for developing the application

• 2017-09-11: Deadline to submit report and repository of the code is 2017-09-07
• 2017-06-19: Deadline to submit report and repository of the code is 2017-06-15
• 2017-07-04: Deadline to submit report and repository of the code is 2017-06-29
• 2017-07-20: Deadline to submit report and repository of the code is 2017-07-17

• VisMaster - Mastering the information age
• Processing: a programming handbook for visual designers and artists. Casey Reas, Ben Fry. MIT Press, 2007
• Design for Information. Isabel Meirelles, Rockport Publisher,2013.
• Interactive Data Visualization for the Web, Scott Murray, O'Reilly Atlas, 2013

• Tools
  • OpenProcessing Classroom
  • Processing.org
  • D3 Javascript Library
  • PiktoChart
  • JS Bin
• Reading Material
  • Data Visualization Resources (on Slideshare)
  • Why Most People's Charts & Graphs Look Like Crap
  • Data + Design (crowdsourced book)
  • Pocket Guide to Writing SVG
• Inspiration
  • http://datavisualization.ch/
  • http://infosthetics.com/
  • http://www.informationisbeautiful.net/
  • http://visualoop.com/
  • http://www.openprocessing.org/
  • Set of images of Processing artwork on Flickr
• Processing libraries
  • Extends sketches with toolbar
  • Utilities
  • Mapping library

• Open Data Tuscany Region
• Sport results
• Flickr Images dataset
• http://www.yelp.com/dataset_challenge
• http://socialcomputing.asu.edu/pages/datasets
• http://networkrepository.com/
• http://chriswhong.com/open-data/foil_nyc_taxi/
• http://www.sociopatterns.org/datasets/
• http://konect.uni-koblenz.de/
• Stanford Large Network Dataset Collection

All exercizes and code discussed during each lesson are available as a Git repository at: https://github.com/rinziv/VA2017

All source code of exercises are available at the URL: https://github.com/VA602AA-master

• Visual Analytics (602AA) - Course Semester 2015
• Visual Analytics (602AA) - Course Semester 2016
• Visual Analytics (602AA) - Course Semester 2017