1 semester

36 hours

Hawthorn

Nil

Credit Points: 12.5 Credit Points

Related Course/s:

A unit of study in the Bachelor of Science (Professional Software Development)

Aims & Objectives:

• describe the key graphical attributes used in data visualisation;
• select and apply appropriate visualisation techniques to a range of data sets;
• compare and contrast the merits and disadvantages of a range of visualisation techniques; 
• calculate data volumes, transfer rates, pixel and fill rates and other hardware parameters in the context of advanced, real-time visualisation;
• write program code (in C or C++) to generate visualisations of data sets;
• create visualisations using advanced display technologies.

Teaching Methods:

Lectures (18 hrs), Tutorial (labs) (18 hrs)

Lectures will cover the introductory and theoretical material in the course. Computer laboratory work will reinforce the lecture material with guided, practical experience and individual project work and assessment exercises.

Assessment:

Examination (40%), written assignments (20%), laboratory-based assessment (40%)

Generic Skills Outcomes:

• Are capable in their chosen professional area. 
• Are entrepreneurial in contributing to innovation and development.

Content:

• History of data visualisation (including scientific method)
• Data types, qualitative vs quantitative data, metadata, file formats, coordinate systems
• Computer graphics for data visualisation
• Graphics hardware: capabilities and specifications
• Low and high-level graphics and visualisation libraries and applications
• 2-d scatter plots and histograms, contour plots, pseudocolour rasters, vector fields
• 3-d scatter plots, isosurfaces, volume rendering, streamlines
• Balancing utility and aesthetics
• Time-evolving data, real-time visualisation, stereoscopic display, ray tracing
• Revision and exam preparation

Reading Materials:

Helen Wright, Introduction to Scientific Visualization, Springer (2007)