Hello, if you have any need, please feel free to consult us, this is my wechat: wx91due
COMP5048 Assignment 2
COMP5048 Visual Analytics 2025 Assignment 2: Group Assignment Deadlines:
● Presentation: Week 11, May 14 WED 11:59pm (Oral Presentation: Week 11-13, 6-9pm)
● Final Report/Individual Report: Week 13, May 29 THU 11:59pm
Choose one data set and produce good visualisations to support analytic tasks of the data.
1. Youtube Trending Videos (https://www.kaggle.com/datasets/canerkonuk/youtube-trending-videos- global)
2. IMDB Movies (https://www.kaggle.com/datasets/asaniczka/tmdb-movies-dataset-2023-930k- movies)
3. Amazon Kindle Books (https://www.kaggle.com/datasets/asaniczka/amazon-kindle-books-dataset- 2023-130k-books)
4. THE World University Rankings (https://www.kaggle.com/datasets/r1chardson/the-world- university-rankings-2011-2023)
5. World Weather Repository (https://www.kaggle.com/datasets/nelgiriyewithana/global-weather- repository)
6. Australian Fatal Road Accident (https://www.kaggle.com/datasets/deepcontractor/australian-fatal- car-accident-data-19892021)
7. Historical Olympic Dataset (https://www.kaggle.com/datasets/muhammadehsan02/126-years-of- historical-olympic-dataset)
8. Spotify High & Low Popularity Tracks (https://www.kaggle.com/datasets/solomonameh/spotify- music-dataset)
9. ATP Professionals Matches (https://www.kaggle.com/datasets/gmadevs/atp-matches-dataset)
10. DBLP Citations (https://www.kaggle.com/datasets/agungpambudi/research-citation-network-5m- papers)
Group Work Instructions: For the selected data set:
1. Design
○ Tasks: Define significant and meaningful tasks based on various aspects of the data:
■ Simple tasks: Overview, simple statistics, e.g., ranking.
■ Middle-level tasks: Identify clusters, correlation, similarity.
■ Complex tasks: Identify relationships, temporal dynamics, comparison.
○ Data processing: Extract subsets from the selected data for each data type:
■ High-dimensional data
■ Graph data
■ Dynamic data
○ Analysis: Analyse these data to support Tasks
○ Visualisation: Visualise each data type to support Visual Analysis
2. Implementation: You can:
○ Use any existing tools
○ Design/implement new algorithms/methods
○ Design/implement a new visual analytic system
○ You must acknowledge all your sources
3. Evaluation: Evaluate how effectively your visualisations support Tasks:
○ Visual analysis, Storytelling, Pros/Cons
4. Demo/Animation of your group’s system/visualisation as a movie
5. For Presentation and Final Report:
○ Each group should extract at least one subset per data type
○ Each group should have at least one collaborative work (for data processing, analysis, visualisation, implementation, demo/animation)
○ Each student should create at least one visualisation
○ Each visualisation should be significantly different from others
6. For Individual Report:
○ Each student should extract at least one different subset per data type
○ Each student should create at least one visualisation per data type
○ The subset/task/visualisation should be significantly different from others in the same group
7. Report Writing: use the correct terminology consistent with the lecture notes
Submission Instructions:
1. Group Presentation (10 marks): Canvas -> Assignment 2 Presentation
● Only one submission per group
● Submit presentation slides in PDF format
● Submit any animation/demo movie in one mp4
Min 11 – Max 15 slides (for 7-8 min presentation): must use the following format/titles:
1. Data set
2. Tasks
3. Data Processing
4. Analysis
5. Visualisation
6. Implementation
7. Evaluation: 1 slide for group work + 3 slides (visualisations of each group member)
8. Planning: plan for weeks 12-13
Marking Rubric: 10 marks
● Quality of Design: task, data processing, analysis, visualisation (3 marks)
● Quality of Implementation (2 marks)
● Quality of Results: Visual analysis, Storytelling (2 marks)
● Quality of Oral Presentation (1.5 marks)
● Quality of System Demo/Animation (1.5 marks)
■ Oral presentation (Week 11-13, 6-9pm): We will assign 20 groups per week.
■ Note: We will use the PDF slide/video submitted at Week 11 (No update allowed).
2. Final Group Report (30 marks): Canvas → Assignment 2 Group Report
● Only one submission per group
● Submit group report + cover page (declare individual contribution with signature) as one PDF
● Submit any animation/demo movie in one mp4
● Submit source codes in a zip file
Min 20 pages in the following format/titles:
1. Introduction
1.1. Data set
1.2. Summary of Contribution
2. Design
2.1. Tasks
2.2. Data Processing
2.3. Analysis
2.4. Visualisation
3. Implementation
4. Evaluation
4.1. Results (for each visualisation)
4.1.1. Visualisation
4.1.2. Visual Analysis, Storytelling
4.1.3. Pros/Cons/Comparison
4.2. Discussion: Summary, Limitation
5. References
6. Appendix (not included in page limit):
6.1. Weekly M eeting M inutes : attendance, discussion, plan (0.5 page per week: week 7 - 12)
6.2. Code
Marking rubric: 30 marks
● Quality of Design: tasks, data processing, analysis and visualisation (6 marks)
● Quality of Implementation (6 marks)
● Quality of Results: visual analysis, storytelling, discussion (9 marks)
● Quality of Writing (5 marks)
● Quality of System Demo/Animation (4 marks)
3. Individual Report (20 marks): Canvas → Assignment 2 Individual Report
● One submission per student
● Submit your individual report with individual cover page as one PDF
● Submit any animation/demo movie in one mp4
● Submit source codes in a zip file
Min 10 pages in the following format:
1. Introduction
1.1. Data Set
1.2. Summary of Contribution
2. Design
2.1. Tasks
2.2. Data Processing
2.3. Analysis
2.4. Visualisation
3. Implementation
4. Evaluation
4.1. Results (for each visualisation)
4.1.1. Visualisation
4.1.2. Visual Analysis, Storytelling
4.1.3. Pros/Cons
4.2. Discussion: Summary, Limitation
5. References
6. Appendix (not included in page limit):
6.1. Individual reflection: progress and plan (3 lines per week: week 7-12)
6.2. Code
Marking rubric: 20 marks
● Quality of Design: tasks, data processing, analysis and visualisation (4 marks)
● Quality of Implementation (3 marks)
● Quality of Results: visual analysis, storytelling, discussion (6 marks)
● Quality of Writing (4 marks)
● Quality of System Demo/Animation (3 marks)