How do we reason about the world, and how do we make sense of the information that is presented to us?
How does human visual perception work, and how do we navigate, interact and evaluate in domains that present information visually. What modalities can we use to represent information about entities and their relationships (e.g. temporal, locative, etc), and how do these modalities impact on human processes?
How do we apply the principles of user and activity centred design to VA systems? How do we design representations that support decision making? How do we determine what relationships in the data sets should be represented? How do we design the interactions that simplify analytical procedures, evidence collation and conclusion formation?
How do we design system architectures that bring together complex data sets so that they can be visualised to support intended applications? This could include areas such as data integrity, data granularity and data provenance.
How do visual analytics systems integrate into real working practices, with particular reference to environments where they will be used for e-Discovery such as complex documentation sets?
Advanced techniques for analysing data sets and extracting knowledge.
In addition, there will be a series of supporting seminars to cover required areas of research methods, mathematical skills and programming.
You can find more information about this course in the programme specification. Module and programme information is indicative and may be subject to change.