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CSC8626 : Data Visualization

  • Offered for Year: 2022/23
  • Module Leader(s): Dr Sara Fernstad
  • Lecturer: Dr Alma Cantu
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus
Semester 1 Credit Value: 10
ECTS Credits: 5.0


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.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture71:007:00Interactive mixed mode Lectures (PiP and online synchronous)
Guided Independent StudyAssessment preparation and completion161:0016:00Zero weight exercise.
Scheduled Learning And Teaching ActivitiesPractical231:0023:00Interactive mixed mode practicals (PiP and online synchronous)
Guided Independent StudyDirected research and reading71:007:00Independent study on course content
Guided Independent StudyProject work471:0047:00Main summative assignment
Teaching Rationale And Relationship

Lectures explain the underpinning principles for the module and technologies that support data visualization. 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 summative submission for the module.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report1M100Written report of the design, implementation & evaluation of the visualisation. Word count: up to 1500; include set of visualization
Zero Weighted Pass/Fail Assessments
Description When Set Comment
Oral ExaminationMStructured discussion inc. a software demonstration & reflection on the key learning objectives of the project work-up to 15 mins
Assessment Rationale And Relationship

The report including visualizations 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.

Reading Lists