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magistraleinformaticaeconomia:va:course2018 [18/02/2019 alle 13:39 (5 anni fa)]
Salvatore Rinzivillo
magistraleinformaticaeconomia:va:course2018 [04/03/2019 alle 12:58 (5 anni fa)] (versione attuale)
Salvatore Rinzivillo
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   * Friday, 14:00 - 16:00, Aula C1 Polo Fibonacci   * 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 ===== ===== Class Calendar =====
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 ===== Previous Editions ===== ===== Previous Editions =====
-  * [[magistraleinformaticaeconomia:va:Course2018]] 
   * [[magistraleinformaticaeconomia:va:Course2017]]   * [[magistraleinformaticaeconomia:va:Course2017]]
   * [[magistraleinformaticaeconomia:va:Course2016]]   * [[magistraleinformaticaeconomia:va:Course2016]]
magistraleinformaticaeconomia/va/course2018.1550497194.txt.gz · Ultima modifica: 18/02/2019 alle 13:39 (5 anni fa) da Salvatore Rinzivillo