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CSC8636 : Complex Data Visualization

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Sara Fernstad
  • Owning School: Computing
  • Teaching Location: Newcastle City Campus

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

Semester 2 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System


Data visualization can be described as the communication of complex data through the use of interactive visual interfaces. It is an increasingly important part of data science and aims to bridge the gap between the human and data, by supporting human perception and cognition to make sense of data analytics outputs.

The aim of this module is to familiarise students with the theoretical underpinnings of visualization techniques for complex data. This module will introduce the research methodology which underpins visualization design and evaluation of visualization approaches. Through project work, students will experience the full lifecycle from design of interactive visualization to evaluation of an advanced visualization approach.

Outline Of Syllabus

The syllabus will cover topics from:
How, why and when to use visualization
The human in the loop – how human perception and cognition influence visualization design.
Approaches to the visualization of complex data, including: Heterogeneous, categorical, ordinal and numerical data;
Multivariate and high dimensional data;
Uncertainty and incomplete data.
Approaches for interactive and multiple coordinated views.
Research methodology and experimental evaluation:
Design studies;
Experimental design;
Usability studies.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture81:008:00Lectures delivered as PIP (with underpinning online material).
Guided Independent StudyAssessment preparation and completion60:303:00Preparation for oral examination
Guided Independent StudyAssessment preparation and completion301:0030:00Project work: Main assessed project
Guided Independent StudyDirected research and reading391:0039:00Lecture follow-up and background reading
Scheduled Learning And Teaching ActivitiesPractical181:0018:00Practical sessions in computer lab, with set exercises and coursework support
Guided Independent StudyReflective learning activity40:302:00Formative exercise
Teaching Rationale And Relationship

Lectures explain the underpinning principles for the module and technologies that support visualization. Lectures are complemented by practical sessions to guide the application of these principles using suitable computational tools.

The practical coursework builds up experience working with advanced visualization challenges using a computational toolset that is used to complete a substantive project. The practical work is documented in a reflective report that constitutes the main submission for the module. The report builds on the lecture work and develops reflection and critical thinking around the application of visualization principles.

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Report2M100Written report details the design of visualization analysis + reflection on alternative approaches and evaluation, based on key learning Max 2,000 word
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
Report1MThe formative assessment builds on the lecture work, providing an opportunity for students to test their understanding of the taught material.
Assessment Rationale And Relationship

The coursework tests the students’ ability to apply visualization techniques to solve a problem to a given specification. The report facilitates and develops reflection and critical thinking around the application of visualization principles and theory, and how they are embedded in the functionality of the application they have developed, we well as critical evaluation of their own work.

Reading Lists