COMP2026 - Visual Analytics
Autumn 2025: Assignment 1
Relational Data Visualisation
(Assignment deadline: Sunday 20/04/2025, 11:59pm on vUWS)
Assignment Details
For this assignment, you are required to identify and develop one (or more) visualisation(s) for relational data sets (such as graphs, networks, and trees as presented in lecture notes in week 3 and week 4) using existing tools, software or your own development using available libraries. You might use the sample datasets at the tutorials as well as the provided visualisation
techniques. Alternatively, you are encouraged to search and use other visualisation tools and/or datasets in the literature. Based on the visualisation(s), you can explore to find insight, patterns, ir(regularity) and interesting properties from the visualisation.
You are also required to write a report (approximately 1000 words and a maximum of 1500 words) on the following aspects:
• Brief technical details of the used visualisation method(s),
• Discussion on the advantages and disadvantages ofthe visualisation method(s) in
comparison with other methods in the literature. Can the visualisation method(s) be used effectively for large relational data sets, and why?
• The visualisations that you develop.
• Discussion on the analysis results and findings on the datasets,
• Discussion on other aspects, literature review of related work and your critical thinking on the visualisation(s).
Note: images (as figures) are essential and should be included in the report to illustrate the visualisations, results and findings. A report with more than 1500 words is not acceptable.
Marking criteria for the assignment include
• Development of visualisations for relational data (60%). You might use existing tools
(e.g. tree visualisations, Gephi, Cytoscape, etc.), existing software libraries (e.g. D3.js) or write your own program in R, Python, Java or any other programming languages. The marking will be based on how well the visualisation methods present the relational data. Interaction should also be included in the visualisation.
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Mark Items
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Percentage
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The developed visualisations
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40%
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The analysis results and findings on the datasets
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20%
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• A report on the technical description of the visualisation, analysis results and other aspects (40%)
• Use of generative artificial intelligence (GenAI) is not permitted in this assessment task without appropriate acknowledgement. See advice on acknowledging the use of generative AI on the Library web page. Working with another person or technology in order to gain an unfair advantage in assessment or improperly obtaining answers from a third party, including generative AI, to questions in an examination or other form of assessment may lead to sanctions under the Student Misconduct Rule. Use of generative AI tools may be detected. More information is available on the Library web page.
• Using GenAI to generate the content is not allowed, and using GenAI for paraphrasing and grammar check might be acceptable but it must be lower than 30%.
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Mark Items
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Percentage
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Brief technical details of the used visualisation method(s).
Discussion on other aspects, literature review of related work and your critical thinking on the visualisation(s).
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15%
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Discussion on the advantages and disadvantages ofthe visualisation method(s) in comparison with other methods in the literature.
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5%
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Present and discuss the developed visualisations
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10%
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Present and discuss analysis results and findings on the datasets
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10%
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Rubrics
Criteria High Distinction Distinction Credit Pass Unsatisfactory
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Develop visualisation method(s) for
relational data (60%)
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Produce an excellent
visualisation method for presenting
relational data. Full interaction is also provided in the
visualisation
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Produce a very good
visualisation method for presenting
relational data. Good interaction is also
provided in the visualisation
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Produce a good
visualisation method for presenting
relational data. Some interaction is also
provided in the visualisation
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Produce a satisfactory visualisation method
for presenting
relational data. Limited interaction is also
provided in the visualisation.
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Not provided OR the provided method does not work according to the requirements
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A short report on the technical contribution and analysis output
(40%)
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Produce an excellent report on the technical contribution and
analysis
outputs/findings (>= 85%)
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Produce a very good report on the technical contribution and
analysis
outputs/findings (75 - 84%)
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Produce a good report on the technical
contribution and analysis
outputs/findings (65 - 74%)
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Produce a satisfactory report on the technical contribution and
analysis
outputs/findings (50 - 64%)
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Not provided OR
produce an
unsatisfactory report on the technical
contribution and analysis
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outputs/findings
(<50%)
Deliverables
Students must individually complete the visualisation(s) and the report. The report should be typed and submitted online through vUWS as a Word or PDF file. A high standard of professional English and neat logical structure (including a consistent and complete referencing style) are expected. The data and source code (if have) should also be submitted on vUWS.
Declaration
You are required to submit a declaration with the following claim (in a text file or world file).
DECLARATION
I hold a copy of this assignment that I can produce if the original is lost or damaged.
I hereby certify that no part of this assignment/product has been copied from any other student’s work or from any other source except where due acknowledgement is made in the assignment.
No part of this assignment/product has been written/produced for me by another person except where such collaboration has been authorised by the subject lecturer/tutor concerned.
Submission
The declaration, visualisation program(s) and datasets, and the report should be submitted via vUWS before the deadline for marking purposes. In the Turnitin submission system, the report (preferably in PDF or MS Word) is submitted separately together with a compressed zip file containing all supporting program(s), data sets or other supporting works. Please ensure the file names include your student id. A submission that does not follow the format is not acceptable. No hard copy of the work and email submission is acceptable.
Important Note
Please note: it is not advisable to copy the materials from illustrating samples, your friend’s works, works from previous years, or other sources. In addition to Turnitin checking, we may run a cross-check of the reports to detect plagiarism. Failure to comply with plagiarism avoidance may lead to misconduct with a serious penalty.