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

• Monday, 16:15 - 18:00, Microsoft Teams
• Friday, 16:15 - 18:00, Microsoft Teams

• 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, vega, etc).
  • The final evaluation will take into account the implementation of a novel, original visualization to present the data in a creative, non-trivial way, using D3.js (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 2014 (https://vacommunity.org/VAST+Challenge+2014). The current VASt Challenge (2021) is using the same structure and mini challenges of the edition of 2014. The data are updated and slightly changed. Students may try to tackle the 2021 challenge.

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. The data of the previous edition has been extended with new data and dimensions. All the data will be made available through an OCG Standard Interface reachable via HTTP. Students interested in the project can send an email to get more details.

• VisMaster - Mastering the information age
• Design for Information. Isabel Meirelles, Rockport Publisher,2013.
• Interactive Data Visualization for the Web, Scott Murray, O'Reilly Atlas, 2013

• Tools
  • D3 Javascript Library
• 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

• 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-2021

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

Recordings of lessons on Microsoft Teams are accessible within the channel of the course.

All source code of exercises are available at the URL: https://github.com/va602aa-2021

• Visual Analytics (602AA) - Course Semester 2020
• Visual Analytics (602AA) - Course Semester 2019
• Visual Analytics (602AA) - Course Semester 2018
• Visual Analytics (602AA) - Course Semester 2017
• Visual Analytics (602AA) - Course Semester 2016
• Visual Analytics (602AA) - Course Semester 2015