Data Visualization & Data Journalism

Credits: 
3
Hours: 
30
Area: 
Big Data Story Telling
Academic Year: 
2023-2024
Description: 

The Data Visualization and Data Journalism course provides a comprehensive introduction to produce effective and efficient visualization and to the practice of data journalism and the art of storytelling through data. During the course, the students will explore the basic of visual encoding and data visualization mapping through encoding with visual variables. They  will also have the opportunity to explore the origin of data journalism, the composition of a newsroom, and a practical way of working. The course will focus on the importance of compelling storytelling in data presentation by mean of exploration of real use case to demonstrate the use of a correct visualization and an engaging storytelling. The "Data Visualization and Data Journalism" course offers students a unique opportunity to develop foundational skills and knowledge to visualize effectively models and data, and present scientific results in journalistic storytelling.
 

Prerequisites: HTML, CSS, and Javascript

Notions: 
  • Introduction to Data Visualization, basic concepts of visual perception, Visual Variables
  • Data Journalism Introduction: principles of communication, what data journalism is, the origins of Data Journalism, newsroom composition and workflow
  • Use cases of good and bad practices of visualizations. Introduction to the library Altair
  • Data Storytelling: why tell stories with data, data story model, storyboarding, how to create more interesting story points
  • Visual Variables and Scales in Altair
  • Case studies of data journalism, data journalism awards
  • Visualization of Geographical Data with Folium
  • Principles of data writing
  • Color models and color scales
  • Data Publishing: Principles of Web Application Design, A sample of a web application layout
     
Competences: 
  • How to encode data and models in an efficient and effective visualization, limiting the impact of cognitive biases.
  • How to design and encode a visual representation through modern data visualization libraries
  • Help to communicate scientific results as a Data Journalism Article (create an interesting story for a declared audience)
  • Design a web application for publishing the Data Journalism article.

Partners