COMP5048 Visual Analytics 2023S1 Assignment 1: Individual work Deadline: April 6 (Week 7) Thursday 23:59pm (pdf on Canvas)
Construct good visualisations of FOUR of the following data to answer the given task.
You can use any suitable layout chosen from the tools assigned to each category.
Create visualisations for each data according to the instructions given.
In your report, explain your justification for your selected visualisation and analysis
methods, then evaluate and compare the pros and cons of your visualisations.
(Note: different tools not listed can be used for analysis before visualising.)
Data: Choose one graph from each category A, B, C, D:
Category A:
For this category, visualise the data using any tool from the following: Tulip, D3
A1: Best-selling albums of 2000s
Visualise the whole tree using TWO different layouts.
Select one label from the data, e.g., could be the most popular label or your favourite, and
extract the subtree rooted at the label.
Visualise the subtree rooted at the selected label.
A2: Best-selling singles of 2000s
Visualise the whole tree using TWO different layouts.
Select one genre from the data, e.g., could be the most popular genre or your favourite, and
extract the subtree rooted at the genre.
Visualise the subtree rooted at the selected genre.
Category B:
For this category, visualise the data using any tool from the following:
yEd, Tulip, Gephi, NetworkX
B1: Composers graph
Analyse the graph to identify the top 150 composers and extract the induced subgraph
containing the top composers.
Visualise the subgraph using TWO different layouts.
Analyse the subgraph using graph analysis methods to identify the most influential
composers and display the analysis results in the visualisation.
B2: TVCG collaboration graph
Analyse the graph to identify the top 150 collaborators and extract the induced subgraph
containing the top collaborators.
Visualise the subgraph using TWO different layouts.
Analyse the subgraph using graph analysis methods to identify the most influential
collaborators and display the analysis results in the visualisation.
Category C:
For this category, visualise the data using any tool from the following: yEd, Tulip, Graphviz
C1: Movie remakes
Analyse the graph to identify the influential directors and movies.
Visualise the graph using TWO different layouts.
Display the analysis results in the visualisation.
C2: Hrafnkels Saga
Analyse the graph to identify the influential characters and relationships.
Visualise the graph using TWO different layouts.
Display the analysis results in the visualisation.
Category D:
For this category, visualise the data using any tool from the following: yEd, Tulip, Gephi, NetworkX, D3
D1: “INFECTIOUS” exhibition interaction network
Analyse the graph to identify the important people and interactions, both in each time slice
and over all time slices.
Visualise the graph, showing all time slices of the graph, using TWO different methods.
Display the analysis results in the visualisation.
D2: Workplace contacts graph
Analyse the graph to identify the important people and interactions, both in each time slice
and over all time slices.
Visualise the graph, showing all time slices of the graph, using TWO different methods.
Display the analysis results in the visualisation.
Submission: Minimum 16 - page report Minimum 4 pages per data:
1st page: 1st Visualisation
2nd page: 2nd Visualisation
3rd-4th pages: Description with the following subheadings:
Design: tools and layouts with justification (design choice)
Analysis: explain analysis methods used with justification on how they support the task
Evaluation: comparison of pros and cons between the two visualisations
Acknowledge all your sources in References
Provide code, if applicable, in Appendix
In Appendix, you can include one more visualisation for each data:
Should be substantially different using different techniques
Include description as above for each alternative visualisation
Add comparison between different visualisations of the same data
Marking Rubric: (5 marks per data; total 20 marks)
Quality of visualisation: 3 marks
Quality of analysis: 1 mark
Quality of evaluation: 1 mark