Visualisation des données et de l'information

• Understand the different types of data that can be viewed.
• Master the elements constituting a graph, their strengths and weaknesses.
• Know the types of graphics available, and how best to use them.
• Be able, based on a set of data and an objective, to choose the visualization that will best convey a message.
• Make the best use of visualization tools to explore a set of data, to understand its essence, the (co-)relationships
• Be able to critically analyze a graph you are confronted with.
• Master the graphing tool studied during the course (ggplot)

•  8 sessions of 3 hours of ex-cathedra courses (to be given via video capsules in 2020-2021 due to the health crisis)
• 3 practical sessions (to be given via Teams in 2020-2021 due to the health crisis)
• a group project to be carried out during the year

Contribution to the teaching profile

For M-JOURR:

CARRYING OUT SCIENTIFIC WORK

• Designing answers
• Collecting, structuring, analyzing and interpreting data and documents
• Format and communicate research results (written and oral expression)
• Develop a clear, precise, structured and well-argued discourse

• Implementing scientific expertise
• Demonstrating critical thinking and autonomy
• Implementing the capacities of analysis, synthesis, contextualization, rigor and coherence

• To critically apply what one has learned and to innovate in order to conduct research independently.
• Collects data and documents using appropriate work instruments and submits them to the appropriate department to the criticism of the data and documents collected
• Formulate hypotheses, analyze, structure and interpret data
• Format and communicate research results (written and oral expression)
• Elaborate a clear and constructed discourse, argue and use the scientific language of the discipline

• Implementing scientific expertise :
• Demonstrating critical thinking and autonomy
• Implementing the capacities of analysis, synthesis, contextualization, rigor and coherence.

References, bibliography, and recommended reading

• Cleveland, W. S., Visualizing data, Murray Hill, Hobart Press, 1993 ;
• Tufte, E., The visual display of quantitative information, Cheshire, Graphics Press, 2001 ;
• Ware, C., Information visualization : Perception for design, San Francisco, Morgan Kaufmann (Elsevier), 2004 (The Morgan Kaufmann Series in Interactive Technologies, 22) ;
• Few, S., Show me the numbers : Designing tables and graphs to enlighten, Oakland, Analytics Press, 2004.

Course notes

• Université virtuelle

Contacts

Sébastien de Valeriola

sebastien.de.valeriola@ulb.be

Campus

Solbosch

Method(s) of evaluation

• written examination
• Written report

written examination

Written report

Examen écrit en session, projet de groupe en cours de semestre

Mark calculation method (including weighting of intermediary marks)

First session: in-session exam: 12/20; group draft: 8/20

Second session: in-session exam: 20/20

Language(s) of evaluation

• french