DidaWiki

Questa pagina è in sola lettura. Puoi visualizzare il sorgente, ma non puoi modificarlo. Contatta l'amministratore se pensi che ci sia un errore.
====== Visual Analytics (602AA) - Course Semester 2022======


===== Schedule =====
  * Monday, 14:15 - 16:00, Microsoft Teams and Room C
  * Wednesday, 14:15 - 16:00, Microsoft Teams and Room L1

===== Exams =====
Students will be admitted to the exam after the registration on the website [[http://esami.unipi.it]]. 
The exam consists of a discussion of the project. It is mandatory to submit a short report (6-10 pages) within the deadline by mail to the instructor, specifying the tag "[VA]" in the subject.

Planned dates:
  * Please log on to the portal for registration to get the next dates


==== Project assignment ====
  * 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.

=== VAST Challenge 2021 :!: **new**===
The project assignment for the exam consists of the realization of a web application addressing data and mini-challenges presented for the VAST challenge 2021 (https://vast-challenge.github.io/2019/index.html). Each student may choose one of the mini-challenges to build a visual interface that answers the proposed questions (see the list on the corresponding page in the VAST website). 


=== Geological data visualization ===
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 this in more detail.

===== Textbooks =====
  * Visual Analytics for Data Scientists. Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Aidan Slingsby, Cagatay Turkay, Stefan Wrobel. Springer, 2020. ISBN: 978-3-030-56146-8 
  * [[http://www.vismaster.eu/news/mastering-the-information-age/|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
  * 
===== Useful Resources =====
  * Tools
    * [[http://d3js.org|D3 Javascript Library]]
    * [[https://vuejs.org/| Vue.js Framework]]
    * [[https://nodejs.org/| Node.js]]
  * Reading Material
    * [[http://www.slideshare.net/AmandaMakulec/data-visualization-resource-guide-september-2014|Data Visualization Resources (on Slideshare)]]
    * [[http://blog.hubspot.com/marketing/data-visualization-mistakes|Why Most People's Charts & Graphs Look Like Crap]]
    * [[https://infoactive.co/data-design/|Data + Design (crowdsourced book)]]
    * [[http://svgpocketguide.com/book/|Pocket Guide to Writing SVG]]
  * Inspiration
    * [[http://datavisualization.ch/]]
    * [[http://infosthetics.com/]]
    * [[http://www.informationisbeautiful.net/]]
    * [[http://visualoop.com/]]

  
===== Class Calendar =====

All exercises and code discussed during each lesson are available as a Git repository at:
https://github.com/va602aa-2022

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.

| ^ Day ^ Aula ^ Topic ^ Learning material ^
^ 01| 2022/02/14 14:15-16:00 | MsTeams - Aula C | Intro: Visual Analytics Process; |{{ :magistraleinformaticaeconomia:va:2022:va_lesson1_introcourse.pdf | Slides}} ; VisMaster Book (Chapter 2) |
^ 02 | 2022/02/19 14:15-16:00 | MsTeams - Aula L1 | Node.js, NPM, Vue.js, GIT | {{ :magistraleinformaticaeconomia:va:2022:va_lesson2_nodejs_npm_git.pdf | Slides}} |
^ 03| 2022/02/21 14:15-16:00 | MsTeams - Aula C | Vision, Perception and effective visualization |{{ :magistraleinformaticaeconomia:va:2021:va_lesson3_vision_perception.pdf | Slides }} |
^ 04 | 2022/02/23 14:15-16:00 | No Lesson | --- | --- |
^ 04 | 2022/02/28 14:15-16:00 | MsTeams - Aula C| Taxonomy of Visual Variables (continued from lesson 3) | {{ :magistraleinformaticaeconomia:va:2021:va_lesson3_vision_perception.pdf | Slides (from lesson 3) }} |
^ 05 | 2022/03/02 14:15-16:00 | MsTeams - Aula L1|  Introduction to HTML, CSS, Javascript | {{ :magistraleinformaticaeconomia:va:2021:va_lesson4_html_css_js.pdf | Slides}} |
^ 06 | 2022/03/07 14:15-16:00 | MsTeams - Aula C | Chart Taxonomies; Do and don'ts  | {{ :magistraleinformaticaeconomia:va:2021:va_lesson7_doanddonts.pdf | Slides}} |
^ 07 | 2022/03/09 14:15-16:00 | MsTeams - Aula L1| Introduction to SVG | {{ :magistraleinformaticaeconomia:va:2021:va_lesson6_svg.pdf | Slides}} |
^ 08 | 2022/03/14 14:15-16:00 | MsTeams - Aula C | Color models and color scales  | {{ :magistraleinformaticaeconomia:va:2021:va_lesson12_colors.pdf | Slides}} |
^ 09 | 2022/03/16 14:15-16:00 | MsTeams - Aula L1 | Intro to D3.js  | {{ :magistraleinformaticaeconomia:va:2021:va_lesson9_d3js_intro.pdf | Slides}} {{https://observablehq.com/d/2b88ad9a53bda15e| Observable Notebook}} |
^ 10 | 2022/03/21 14:15-16:00 | MsTeams - Aula C | Scale functions  | {{ :magistraleinformaticaeconomia:va:2021:va_lesson8_scales.pdf | Slides}} |
^ 11 | 2022/03/23 14:15-16:00 | MsTeams - Aula L1 | Continuation of D3.js  Introduction | {{ :magistraleinformaticaeconomia:va:2021:va_lesson9_d3js_intro.pdf | Slides}} {{https://observablehq.com/d/2b88ad9a53bda15e| Observable Notebook}} |
^ 13 | 2022/03/28 14:15-16:00 | MsTeams - Aula C | Visualizing Hierarchies  | {{ :magistraleinformaticaeconomia:va:2021:va_lesson12_hierarchies.pdf | Slides }} |
^ 14 | 2022/03/30 14:15-16:00 | MsTeams - Aula L1 | Reusable D3.js Components  | {{ :magistraleinformaticaeconomia:va:va_lesson11_reusable_modules.pdf | Slides }}, {{ https://observablehq.com/@rinziv/my-second-visualization-in-d3-js?collection=@rinziv/va602aa | Notebook 1}} {{ https://observablehq.com/@rinziv/my-third-visualization-in-d3-js?collection=@rinziv/va602aa| Notebook 2}} {{https://observablehq.com/@rinziv/my-reusable-visualization-in-d3-js?collection=@rinziv/va602aa | Notebook 3}}|





===== Previous Editions =====
  * [[magistraleinformaticaeconomia:va:Course2021]]
  * [[magistraleinformaticaeconomia:va:Course2020]]
  * [[magistraleinformaticaeconomia:va:Course2019]]
  * [[magistraleinformaticaeconomia:va:Course2018]]
  * [[magistraleinformaticaeconomia:va:Course2017]]
  * [[magistraleinformaticaeconomia:va:Course2016]]
  * [[magistraleinformaticaeconomia:va:Course2015]]