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--- magistraleinformaticaeconomia:va:course2018 [18/02/2019 alle 13:39 (6 anni fa)] – creata Salvatore Rinzivillo
+++ magistraleinformaticaeconomia:va:course2018 [04/03/2019 alle 12:58 (6 anni fa)] (versione attuale) – Salvatore Rinzivillo
@@ Linea 1: / Linea 1: @@
-====== Visual Analytics (602AA)======
+====== Visual Analytics (602AA) - Course Semester 2018======
   * **Salvatore Rinzivillo** ([[rinzivillo@isti.cnr.it]])
@@ Linea 7: / Linea 7: @@
   * Friday, 14:00 - 16:00, Aula C1 Polo Fibonacci
-===== News =====
-To keep updated with the last news of the course, subscribe at the Telegram channel: https://t.me/va602aa
-  * **[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
-===== Exams =====
-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.
-==== 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 (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.
-=== VAST Challenge 2017 ===
-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.
-== Rules ==
-   * 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
-=== Didactic Data Mining ===
-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.
-== Rules ==
-     * 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
-=== Network Diffusion Library ===
-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.
-== Rules ==
-  * 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
-==== Next Exams ====
-  * **2018-09-10**: Deadline to submit report and repository of the code is 2018-09-06
-  * <del>**2018-07-09**: Deadline to submit report and repository of the code is 2018-07-05</del>
-  * <del>**2018-06-18**: Deadline to submit report and repository of the code is 2018-06-14</del>
-===== Textbooks =====
-  * [[http://www.vismaster.eu/news/mastering-the-information-age/|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
-===== Useful Resources =====
-  * Tools
-    * [[http://www.openprocessing.org/classroom/4698| OpenProcessing Classroom]]
-    * [[http://processing.org|Processing.org]]
-    * [[http://d3js.org|D3 Javascript Library]]
-    * [[http://piktochart.com/|PiktoChart]]
-    * [[http://jsbin.com/|JS Bin]]
-  * 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/]]
-    * [[http://www.openprocessing.org/]]
-    * [[https://www.flickr.com/groups/processing/|Set of images of Processing artwork on Flickr]]
-  * Processing libraries
-    * [[http://www.sojamo.de/libraries/controlP5/|Extends sketches with toolbar]]
-    * [[http://toxiclibs.org/|Utilities]]
-    * [[http://unfoldingmaps.org/|Mapping library]]
-==== Other resources ====
-  * [[http://dati.toscana.it|Open Data Tuscany Region]]
-  * [[http://riccomini.name/posts/game-time-baby/|Sport results]]
-  * [[http://yahoolabs.tumblr.com/post/89783581601/one-hundred-million-creative-commons-flickr-images|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/]]
-  * [[http://snap.stanford.edu/data/|Stanford Large Network Dataset Collection]]
 ===== Class Calendar =====
@@ Linea 152: / Linea 45: @@
 ===== Previous Editions =====
-  * [[magistraleinformaticaeconomia:va:Course2018]]
   * [[magistraleinformaticaeconomia:va:Course2017]]
   * [[magistraleinformaticaeconomia:va:Course2016]]