Data Visualisation: 2023-2024
OverviewWell-designed visualisations capitalise on human facilities for processing visual information and thereby improve comprehension, memory, inference, and decision making. In addition, the advent of the so-call “explosion of Big Data” has increased the needs of effective visualisation systems for data analysis and communication. In this course we will study techniques and algorithms for creating effective visualisations based on principles from graphic design, visual art, perceptual psychology, and cognitive science. The course is targeted both towards students interested in using visualisation in their own work, as well as students interested in building better visualisation tools and systems.
The lectures outlined below have been designed so that, by the end of course, students will have:
• an understanding of key visualization techniques and theory, including data models, graphical perception and methods for visual encoding and interaction.
• exposure to a number of common data domains and corresponding analysis tasks, including exploratory data analysis and network analysis.
• practical experience building and evaluating visualisation systems.
Students are formally asked for feedback at the end of the course. Students can also submit feedback at any point here. Feedback received here will go to the Head of Academic Administration, and will be dealt with confidentially when being passed on further. All feedback is welcome.
Taking our courses
Matriculated University of Oxford students who are interested in taking this course, or others in the Department of Computer Science, must complete this online form by 17.00 on Friday of 0th week of term in which the course is taught. Late requests, and requests sent by email, will not be considered. All requests must be approved by the relevant Computer Science departmental committee and can only be submitted using this form. Priority will be given to students studying for degrees in the Department of Computer Science.