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

• Monday, 16:00 - 18:00, Aula L1 Polo Fibonacci
• Friday, 16:00 - 18:00, Aula C1 Polo Fibonacci

To keep updated with the last news of the course, subscribe at the Telegram channel: https://t.me/va602aa

• [new] 2020-04-06: The lesson for today April 6th is canceled. Next lesson will be on Friday, April 17th, 2020
• The class on March 6th is canceled. The next lesson on Monday, March 9th from 16 to 18 will be kept on the group on Microsoft Teams. Please check that you have access to the platform. For any problem, please refer to the following instructions: https://www.unipi.it/index.php/docenti2/item/17671-corsi-online.
• The new edition is starting on Monday 17th February 2020 at 16:00 in Aula L1

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 (plot.ly, 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). You can refer to visualization techniques already present in the literature, by adapting or implementing part of the solution.
  • Interactivity should be implemented, providing toolbars, selections, and filters for the data.
  • The visual widget should interact among them, realizing a set of linked displays 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 a description of the 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 consists of the realization of a web application addressing data and mini-challenges presented for the VAST challenge 2019 (https://vast-challenge.github.io/2019/index.html).

This project has the objective of creating a visual dashboard to explore and browse geographical and geological data. This is a joint project with the IGG institute of CNR. Data available for the project can not be shared publicly. If interested, send me an email to fix a meeting to discuss more in detail.

• 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 exercises and code discussed during each lesson are available as a Git repository at: https://github.com/va602aa-2020

A collection of Observable Notebooks are available at: https://observablehq.com/collection/@rinziv/va602aa

Recordings of lessons on Microsoft Teams are accessible here: https://web.microsoftstream.com/channel/a6b5e3aa-623d-435e-8601-419537901839
Follow the channel to be updated when new videos are published.

All source code of exercises are available at the URL: https://github.com/va602aa-2020

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