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Module: Data Analytics and Visualization

Academic Year: 2020-2021

Title: Graph Analysis of Air Transport Network 

The assignment should be submitted electronically as a pdf, in the form of a brief individual report (2500 words limit applies) explaining the methods and giving a clear statement of the principal results.  Students should highlight the physical basis for any assumptions made wherever possible.

The final completed assignment should be submitted to Turnitin following the standard procedure on or before the submission date.

You are reminded that in the absence of exceptional circumstances (supported by written evidence) late submissions will be penalised.

Aim

The aim of this study is to select, apply and study network data analysis across different graph scales using passenger flight data.

Problem Definition

Many large data sets have a network dimensionality (social networks, peer-to-peer file transfer, bit coin, organisation, supply chain, connected systems…etc.). Practical applications of network analysis include understanding its resilience to disturbances, robustness to attacks, and efficiency of processes on networks (information, energy transfer). The techniques draw knowledge from applied statistics, applied physics, graph theory, and data science. More recent advances have developed graph neural networks to discover graph features to quantify challenging behaviour.

In this case you’re to apply classic feature-based graph analysis to flight data to demonstrate multi-scale graph analysis covered in the lectures. The aim is to represent important notions in a low data dimension to enable effective communication and dissemination.

The objectives of this works are as follows:

1. Transform flight data into network form.

2. Implement graph analysis across 3 different scales: 1) macro-scale, 2) meso-scale, 3) node-level.

3. Assess and discuss the 3 different graph analysis scales and what they mean for air transport networks.

Data

The dataset is given on Canvas - contains domestic flight data for 1 month across different countries in the world. An example of the image from the database is shown below.

Figure 1 Example of domestic flight network for USA.

Methodology

To achieve the objectives of this work you need to select various graph analysis methods across the scales (node to community to overall structure), justifying pros and cons in comparison with other methods (500 words max).

It is anticipated that one of the methods from the scope of the materials taught in the module will be implemented for analysis purposes, following the above selection process.

The method should be implemented to the data sets of the following countries: USA, China, UK, and Australia.

Any analysis tools are permitted – there is no requirement to use MATLAB/R/Gephi/Python or any other tool, but it is recommended to include the code in the report to enable markers to see possible reasons for the problems with the results (if this happens) to be accounted for during the marking process.

The word count for the report is low (2000 words, excluding references), therefore, results and discussion should be predominantly presented in the graphical or tabulated way. Reproduction of the problem statement and data description will not be included in the word count.

Assignment report should be prepared using the supplied template.

Assessment

Assignment marking will be focused on the ability discuss the appropriateness of the graph techniques with the following selection and quality of the results assessment. A part of the marks will be allocated for implementation efforts and results obtained.

Use of the programming languages or tools is not assessed, i.e. type of the tool used or length of the code will not affect marks. Problem statement and data description (in case they are included in the report) will not be assessed too.

The marks for the assignment will be distributed as follows:

1. Construct separate airline networks for each country (internal flights only) and visualise them using geospatial coordinates provided. Comment on your how it is done. (250 words max)

 [15 Marks]

2. Plot the following:

a) Degree distribution (x-axis: descending rank, y-axis: logscale of weighted degree). [5 marks]
b) Degree vs. betweenness distribution [10 marks]

c) Assortativity (degree correlation)  [5 marks]

d) Core community size [20 marks]

[Total: 40 Marks]

3. Analysis, discussion and conclusions that include selection and application of metrics for analysis [10 marks], with performance considerations [5 marks]. Hypothesize with evidence on the potential impact of results on the design of future aircrafts in these different countries [15 marks]

 [Total: 30 Marks]

4. Style and presentation that include presence of logical structure, appropriate citation style (if references used), quality of graphical material (labels, legends, titles and captions as appropriate), readability of the text material, clarity of results presentation in the text.

a) Structure [5 marks],

b) Clarity [10 marks].

[Total: 15 Marks]

Marking rubric