CSC8626 : Data Visualization
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
Semesters
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 | |
Pre-requisite
Modules you must have done previously to study this module
Pre Requisite Comment
N/A
Co-Requisite
Modules you need to take at the same time
Co Requisite Comment
N/A
Aims
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.
Learning Outcomes
Intended Knowledge Outcomes
Knowledge of key topics in data visualization 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.
• Approaches to evaluating the speed and effectiveness of visualization techniques.
Intended Skill Outcomes
Demonstrate an ability to:
• Prepare data sets for visualization.
• Select appropriate visualization approaches for common types of data.
• Implement visualizations using a current visualization toolset.
• Layout and implement a dashboard.
• Critically evaluate the performance and evaluation of a visualization.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Scheduled Learning And Teaching Activities | Lecture | 10 | 1:00 | 10:00 | PIP Lectures (underpinned by online material). |
| Scheduled Learning And Teaching Activities | Practical | 9 | 2:00 | 18:00 | PIP practical work in computer classrooms with set exercises and coursework support. |
| Guided Independent Study | Directed research and reading | 32 | 1:00 | 32:00 | Independent study on course content |
| Guided Independent Study | Project work | 40 | 1:00 | 40:00 | Main summative assignment: written report of the design, implementation & evaluation of the visualisation include set of visualization and short video. Word count: up to 1500 |
| Total | 100:00 |
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.
Reading Lists
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 1 | M | 100 | Written 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 log | M | Source 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 exercises | 1 | M | Quiz 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.
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- CSC8626's Timetable
Past Exam Papers
- Exam Papers Online : www.ncl.ac.uk/exam.papers/
- CSC8626's past Exam Papers
General Notes
N/A
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Disclaimer
The information contained within the Module Catalogue relates to the 2024 academic year.
In accordance with University Terms and Conditions, the University makes all reasonable efforts to deliver the modules as described.
Modules may be amended on an annual basis to take account of changing staff expertise, developments in the discipline, the requirements of external bodies and partners, and student feedback. Module information for the 2025/26 entry will be published here in early-April 2025. Queries about information in the Module Catalogue should in the first instance be addressed to your School Office.