Run by School of Computer Science and Electronic Engineering
20.000 Credits or 10.000 ECTS Credits
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.
Indicative content includes:
- 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.
- Understand current visualisation techniques, including traditional plots (bar, line, scatter etc.), parallel coordinate plots, treemaps, re-orderable matrix; scatter plot matrix.
- Perception and interpretation; understanding how humans perceive information. Encoding of value; Encoding of relation; Models: Bertin, Mackinlay (Quantitative, Ordinal, and Categorical), Semiotics.
- Design of visualisations, dashboards, and considering alternative solutions and critical analysis of these visualisations.
- Interaction and exploration, looking at focus + context and distortion technique; multiple views and composite interaction; brushing; animation.
Equivalent to 50%. Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.
Equivalent to the range 60%-69%. Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.
Equivalent to the range 70%+. Assemble critically evaluated, relevent areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.
Critically evaluate Information Visualization techniques and suitability for a given purpose.
Apply information visualization techniques (Representation, Presentation, and Interaction) to develop new visualization techniques.
Evaluate and develop alternative visualization design solutions through sketching and planning.
Describe different aspects of data, identify, analyse and evaluate component parts.
Select appropriate interation techniques for a particular context.
|WRITTEN PLAN||Technical design plan||
Technical design plan, demonstrating an in depth knowledge of visualisation encoding schemes, understanding and consideration and balanced critique of alternative design strategies.
|COURSEWORK||Visualisation implementation and evaluation||
Delivery of a suitable visualisation tool that displays given data, allows user to interact with the data, along with a video presentation/demonstration of the work and critical reflection thereof.
Teaching and Learning Strategy
Traditional lectures (1 hr x 24 weeks)
Lab based exercises and group discussions, 1 per week.
Tutor-directed private study including individual assessments.
- Literacy - Proficiency in reading and writing through a variety of media
- Numeracy - Proficiency in using numbers at appropriate levels of accuracy
- Computer Literacy - Proficiency in using a varied range of computer software
- 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
- 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
- Apply knowledge and understanding of the specialist cognate area of computer systems engineering in an international context;
- Formulate and analyse requirements and practical constraints of products, processes and services, place them in an engineering context and manage their implementation;
- Solve problems logically and systematically;
- Assess and choose optimal methods and approaches for the specification, design, implementation and evaluation of engineering solutions.
- Plan, budget, organise and manage people and resources;
- Agree objectives and work plans with individuals;
- Analyse and display data using appropriate methods and mathematical techniques;
- Deploy theory in design, implementation and evaluation of systems
- Specify, design or construct computer-based systems
- Deploy tools effectively
- Development of general transferable skills
- System Design
- Knowledge and/or understanding of appropriate scientific and engineering principles