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CS142 Visualisation

CS142 15 CATS (7.5 ECTS) Term 2


Option - CS, CSBS and DM

Learning Outcomes

On completion of the module the student should be able to:

  • Understand and demonstrate the core skills required to effectively visualise information and processes.
  • Explore procedures, data and emergent systems as the subject of visualisations.
  • Demonstrate an understanding of visualisations and their usage in a wide variety of applications.
  • Evaluate visualisations in terms of users and tasks, and human factors.


  • Introduction
  • How visualisations convey information
  • Principles and tecniques for creating effective visualisations
  • Mapping information to images
  • Limits of visualisation
  • Ethical challenges
  • Visualising algorithms e.g. travelling salesman problem, Dijkstra's algorithm, graph drawing, voronoi diagrams, geometric tessellation
  • Visualising data sets, e.g. DNA sequences, sound files or a collection of tweets
  • Coding natural systems e.g. cellular automata, flocking, reaction-diffusion systems and computationial biology applications
  • Processing as a tool for visualising information


  • Reas, C. and Fry, B. (2014) Processing: A Programming Handbook for Visual Designers (Second Edition) MIT Press.
  • Schiffman, D. (2012) The Nature of Code: Simulating Natural Systems with Processing.
  • Tufte, ER. (2001) The visual display of Quantative Information
  • Sedgewick, R and Wayne, K. (2011) Algorithms (Second Edition)


Assessed coursework (100%)


20 one-hour lectures
10 two-hour lab sessions.