CSC8626 : Data Visualization
- Offered for Year: 2019/20
- Module Leader(s): Professor Nick Holliman
- Owning School: Computing
- Teaching Location: Newcastle City Campus
|Semester 1 Credit Value:||10|
Data visualization systems create visual representations of datasets designed to help people carry out tasks more quickly or more effectively. These systems form a critical link between data analytics outputs and the human perception and cognition of the meaning of those outputs.
The aim of this module is to introduce students to the theoretical underpinnings of the subject and allow them to build skills in the practice of creating data visualizations.
Outline Of Syllabus
The syllabus will cover topics from:
• Data abstraction – the types and semantics of data.
• Task abstraction – the uses for and targets of visualization.
• Human perception and cognition and how it influences the design of visual representations of data.
• Approaches to the visualization of categorical, ordinal and numerical data.
• The visualization of geographic and time series data.
• Dashboards, reasons for creating, layout design.
• Critical evaluation of the speed and effectiveness of visualization techniques.
|Scheduled Learning And Teaching Activities||Lecture||7||1:00||7:00||Lectures|
|Guided Independent Study||Assessment preparation and completion||1||0:30||0:30||Oral Examination|
|Guided Independent Study||Assessment preparation and completion||4||0:30||2:00||Preparation for oral examination|
|Guided Independent Study||Assessment preparation and completion||16||1:00||16:00||Two short formative exercises|
|Guided Independent Study||Directed research and reading||7||1:00||7:00||Lecture follow-up|
|Scheduled Learning And Teaching Activities||Practical||17||1:00||17:00||Practical sessions|
|Guided Independent Study||Directed research and reading||20||1:00||20:00||Background reading|
|Guided Independent Study||Project work||30||1:00||30:00||Main assessed project|
|Scheduled Learning And Teaching Activities||Dissertation/project related supervision||2||0:15||0:30||Up to two 15 min drop-in sessions|
Teaching Rationale And Relationship
Lectures explain the underpinning principles for the module and technologies that support data visualisation. Lectures are complemented by supervised practical sessions to guide the application of these principles using suitable computational tools. The practical work builds up experience working with a computational toolset that is used to complete a substantive project that is documented in a report that constitutes the main submission for the module.
The format of resits will be determined by the Board of Examiners
|Report||1||M||100||Written report details the design, implementation & evaluation of the visualisation. Word count: up to 2,000 words|
Zero Weighted Pass/Fail Assessments
|Oral Examination||M||Structured discussion inc. a software demonstration and reflection on the key learning objectives of the project work-up to 20 mins|
Assessment Rationale And Relationship
The report tests the students’ ability to apply visualisation techniques to solve a problem to a given specification. The semi-structured interview facilitates a reflective discussion about how individual students have met the learning objectives of the module and how the principles of visualisation are embedded in the functionality of the application they developed.