Module ICP-4142:
Information Visualization

Module Facts

Run by Computer Science

15 Credits or 7.5 ECTS Credits

Semester 1

Organiser: Prof Jonathan Roberts

Overall aims and purpose

Information Visualization (IV) focuses on the use of visualization techniques to help users understand and analyze non-scientific and abstract data. Such abstract data includes numerical data in tabular form, textual information and associative (network) sources, and contain multiple variables. The aim of this course is to introduce principles of information visualization, develop IV critiquing skills, learn about different Information Visualization designs, and gain foundational skills to design new innovative Information Visualisations through planning by sketching and implementation of those designs.

Course content

  • The history and future of Information Visualization; the challenges of Information Visualization; tasks; user, perception, data types.
  • Looking at data. Data capture and problems of capturing data. Selection/abstraction of data (aggregation, sampling; binning; cropping); Big data challenges.
  • Perception and interpretation; Encoding of value; Encoding of relation; Models: Bertin, Mackinlay (Quantitative, Ordinal, and Categorical), Semiotics.
  • Design of new visualisations, and considering alternative solutions (using sketching and the Five Design Sheets as a planning method) and critical analysis of these visualisations.
  • Current visualisation designs, including traditional plots (bar, line, scatter etc.), parallel coordinate plots, treemaps, re-orderable matrix; scatter plot matrix.
  • Interaction and exploration, looking at focus + context and distortion technique; multiple views and composite interaction; brushing; animation.

Learning outcomes mapped to assessment criteria







In-depth knowledge and comprehension of Information Visualization (encoding) techniques and be able to explain and illustrate different visualisation algorithms, and recognise and discuss their advantages and disadvantages.

A good knowledge of encoding techniques for Information Visualization Able to analyse and combine various models and theories, to apply to a sophisticated application. An in-depth knowledge of encoding techniques. Very good knowledge of Bertin’s model.

To demonstrate in-depth understanding of Interaction techniques for Information Visualization. Be able to assess a given situation, choose and justify a suitable interaction technique for the task.

Understands well the main Information Visualization interaction methods. In-depth knowledge of information visualization interaction and their advantages and disadvantages and how they can be applied. Very good knowledge of the visualization techniques; can understand and manipulate non-trivial information visualizations.

Apply information visualization techniques (Representation, Presentation, and Interaction) to develop new visualization techniques. To be able to plan, analyse and examine given data, formulate many different (potential) solutions and construct a new visualisation solution,

Good understanding of the issues involved in applying information visualization design. An understanding of the principles of the FdS methodology. Able to use and discuss a wide range of information visualization techniques and issues involved in Information Visualization. An excellent understanding, design and implementation of a visualization using the FdS strategy. Very good knowledge of development issues, and ability to use many techniques. A good understanding and application of visualization techniques through the FdS methodology.

Be able to critique and develop alternative (potential) visualization design solutions through sketching and planning. To justify the suitability of decisions made, and reflect on the individual parts and the final design.

Excellent discussion and well-considered critical evaluation and reflection of alternatives, and a clear argued presentation of alternative potential solutions. A good critical ability, and consideration of different ideas, and discussion of ideas, and through critical reflection. Very well-argued viewpoint of good/bad visual depictions and demonstration of different solutions, and presentation through sketching.

In depth understanding of data for the purpose of data-visualisation. To understand issues from size (e.g., big data) to types of data, to be able to categorise data, and to distinguish dependent and independent data, and manage data effectively.

A good understanding of different aspects of data, as they relate to data-visualisation. Well argued understanding and demonstration of different data types, clear demonstrable knowledge of dependent and interdependent variables. Enable to manage data well, and realise the potential of the data. Exceptional demonstration of data manipulation, e.g., clear presentation of unknown knowledge from data.

Assessment Methods

Type Name Description Weight
Examination 50
Assignment 1 - FdS design 10
Assessment 2 - visualization tool & critique 40

Teaching and Learning Strategy


24 hours over 12 weeks


12 hours over 12 weeks, including discussions, and exercises and demonstrations.

Private study 114

Transferable skills

  • Literacy - Proficiency in reading and writing through a variety of media
  • Numeracy - Proficiency in using numbers at appropriate levels of accuracy
  • Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
  • Exploring - Able to investigate, research and consider alternatives
  • Information retrieval - Able to access different and multiple sources of information
  • Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
  • Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.
  • Presentation - Able to clearly present information and explanations to an audience. Through the written or oral mode of communication accurately and concisely.
  • Argument - Able to put forward, debate and justify an opinion or a course of action, with an individual or in a wider group setting
  • Self-awareness & Reflectivity - Having an awareness of your own strengths, weaknesses, aims and objectives. Able to regularly review, evaluate and reflect upon the performance of yourself and others

Subject specific skills

  • Knowledge and understanding of facts, concepts, principles & theories
  • Use of such knowledge in modelling and design
  • Problem solving strategies
  • Deploy theory in design, implementation and evaluation of systems
  • Deploy tools effectively
  • Development of general transferable skills
  • Deploy systems to meet business goals
  • Defining problems, managing design process and evaluating outcomes
  • System Design
  • Knowledge and/or understanding of appropriate scientific and engineering principles
  • Knowledge and understanding of mathematical principles
  • Principles of appropriate supporting engineering and scientific disciplines

Courses including this module