Module overview
Data visualisation is the process of summarising and communicating the information in a dataset through graphics. This course examines what makes good visualisations, and how this depends on the audience and purpose of the visualisation and the type of data being displayed. The link between good graphics and an understanding of human perceptual and information-processing capacities are discussed. These principles are put into practice by using the R programming language to construct and deploy high quality visualisations.
Aims and Objectives
Learning Outcomes
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- construct effective data visualisations, including both static and interactive visualisations.
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- the principles of information design;
- the principles of interaction design.
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- critically assess different methods of data visualisation and select one appropriate for a particular purpose and audience.
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- interpret and criticise data visualisations, and identify those that are misleading.
Syllabus
- Principles of information design
- Graphical typology
- Tools for data visualisation
- The grammar of graphics
- Principles of interaction design
- Visualisation on the web
- Interactive visualisation in R and Shiny
- Report automation and dashboards using R and markdown.
Learning and Teaching
Teaching and learning methods
Depending on feasibility, teaching may be delivered face to face intensively over a week, or online using a mixture of synchronous and asynchronous online methods, which may include lectures, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study.
Type | Hours |
---|---|
Teaching | 27 |
Independent Study | 73 |
Total study time | 100 |
Assessment
Assessment strategy
100% Coursework
Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Assignment | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Assignment | 100% |
Repeat Information
Repeat type: Internal & External