Information visualisation

Teacher(s)

Lee John;

Language

English
> French-friendly

Content

·         What and why information visualisation?
·         Data abstraction: types of data and of datasets
·         Which visualisation for which task?
·         Validating visualisations
·         Display and ocular perception
·         Visualisation channels (colour, size, shape, angle, ...)
·         Tabular data: lists, matrices, tensors
·         Spatial data: scalar, vector and tensor fields
·         Networks and trees
·         Link between machine learning and visualisation: clustering, dimensionality reduction, graph embedding
·         Interactive visualisation
·         Multiple views
·         Advanced topics in visualisation

Teaching methods

Lectures in classroom, practical sessions on computers, project as homework plus Q&A sessions.

Evaluation methods

Oral examination with preparation time. Interrogation on the course material and about the project realization.
The examination grade is split into 10/20 for the course and 10/20 for the project.
A project report must be handed in as a condition to take the exam.

Online resources

Moodle page of the course: https://moodle.uclouvain.be/course/view.php?id=3502

Bibliography

Visualization analysis & Design, Tamara Munzner, CRC Press, 2015.

Teaching materials

• Slides of the course, available on Moodle

Faculty or entity

> EPL