Course co-ordinator(s): Dr Pierre Le Bras (Edinburgh), Dr Ryad Soobany (Dubai), Radu-Casian Mihailescu (Dubai), Dr Abdullah Almasri (Malaysia).
Aims:
To provide students with the theory, principles and tools to enable them:
- To create engaging and intuitive graphical and interactive applications that allow users to search, explore, reveal, partition, understand, discover and communicate the structure and information in large data sets;
- To convey ideas effectively, considering both aesthetic form and required functionality that will provide insights into different types of dataset (structured and unstructured);
- To stimulate user engagement, attention and discovery;
- To be able to implement interactive web-based visualisation systems and assess their effectiveness.
Detailed Information
Course Description: Link to Official Course Descriptor.
Pre-requisites: Numeracy and basic OO programming ability (3rd year CS).
Location: Dubai, Edinburgh.
Semester: 2.
Syllabus:
Overall aims:
- Use case scenarios (browsing, search, engagement, summarisation, brain storming)
- Example data sets and visualisations.
- Design principles and Data source types
- D3 JavaScript library and programming
- Data, information and display/infographic types (bar, pie, tree, pack, line, map)
- Abstraction methods including clustering, topic modelling, dimensional reduction
- Interaction (exploration, browsing, filtering, focussing
- Project requirements (D3 web application)
Learning Outcomes: Subject Mastery
Understanding, Knowledge and Cognitive Skills Scholarship, Enquiry and Research (Research-Informed Learning)
- A detailed and integrated knowledge and understanding of the data visualisation and data analysis processes.
- Extensive knowledge of different infographic types, interactivity and design choices.
- Extensive knowledge of different information and data types.
- Demonstrate a critical awareness of the main types of information and the appropriateness and effectiveness of associated visualisation and analysis techniques.
- Ability to understand requirements of different user groups and be able to adapt visualisations accordingly
Learning Outcomes: Personal Abilities
Industrial, Commercial & Professional Practice Autonomy, Accountability & Working with Others Communication, Numeracy & ICT
- Rational problem identification, conceptualisation and definition.
- Ability to deal with complex issues and apply critical analysis and solution selection.
- Exercise substantial autonomy, initiative, and creativity in the application of data visualisation & analysis techniques.
- Demonstrate critical reflection on system development and performance (PDP).
- Communicate with peers, senior colleagues and specialists (PDP).
SCQF Level: 11.
Credits: 15.