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CSC8626 : Data Visualization

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Alma Cantu
  • Lecturer: Dr Daniel Archambault
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus

Your programme is made up of credits, the total differs on programme to programme.

Semester 1 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System


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 ActivitiesLecture101:0010:00PIP Lectures (underpinned by online material).
Guided Independent StudyDirected research and reading321:0032:00Independent study on course content
Scheduled Learning And Teaching ActivitiesPractical92:0018:00PIP practical work in computer classrooms with set exercises and coursework support.
Guided Independent StudyProject work401:0040:00Main summative assignment: written report of the design, implementation & evaluation of the visualisation include set of visualization and short video. Word count: up to 1500
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 and short pre-recorded video.
Zero Weighted Pass/Fail Assessments
Description When Set Comment
Reflective logMSource code of the visualization project.
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Prob solv exercises1MQuiz on lecture content to support coursework
Assessment Rationale And Relationship

The assessment is based on case studies, using real world data, allowing students to explore practical application of the techniques and theories that have learned. The report including visualizations and video demonstration tests the students’ ability to apply visualisation and interaction techniques to solve a problem to a given specification. Problem solving exercise quiz to support coursework by giving feedback to students.

Reading Lists