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PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

Problem & Motivation

Flight delays has been a very common problem for travelers, the delay can be attributable to various problems, such as, aircraft issues, weather issues at origin airport or/and destination airport. The delay has no doubts will disappoint air travelers and affect their flight experience greatly. Thus, in this project, our team aims to investigate the performance of different airlines and flight delays in detail.

In addition, airport network is a very critical and complex transportation infrastructure for a nation, it is increasingly important for public policy considerations. The disruptions of the airport network, caused by terrorist attack, disease transmission or other reasons, can lead to huge economic loss. Thus, the study on the airport network can assist us better understand the relationship between different airports, for example, identify most critical airport, and take proactive measures to prevent occurrence of disruptions.

Objectives

In this project, we will adopt visualization techniques to:

• Demographics of student alcohol consumptionAnalyse airport network connectivity
• Analyse flight delays for different airlines
• Evaluate on-time performance for airlines and aircrafts

With the visualization, airline companies will become aware of its on-time performance among all airlines and meanwhile have a better idea on areas where greater attention should be placed on routine operation, such as service or aircraft maintenance. Our visualization will also provide a detailed insight on airport network, it will speed up the decision making process when faced with infectious diseases and terrorist attacks.

Selected Dataset

We have obtained the dataset from Kaggle, which can be download from https://www.kaggle.com/usdot/flight-delays/data

Dataset/Source	Data Attributes	Rationale Of Usage
airline.csv	IATA_Code, String, Airline identifier Airline, String, Airport Name	This data is used to identify and provide detailed information about the different airlines.
airport.csv	IATA_Code, String, Location identifier Airport, String, Airport Name City, String, City of Airport State, String, State of Airport Country, String, State of Airport Latitude, Numeric, Latitude of the Airport Longitude, Numeric, Longitude of the Airport	This data is used to identify and provide detailed information about different airport. It complements the main dataset by providing detailed location information about latitude and longitude, city, state and country of the airport.
flights.csv	Year, Numeric, Year of the flight Month, Numeric, Month of the flight Day, Numeric, Day of the flight Day_of_Week, Numeric, Day of week of the flight Airline, String, Airline identifier Tail_Number, String, Aircraft identifier Origin_Airport, String, Departing airport Destination_Airport, String, Destination airport Departure_Delary, Numeric, Total delay on Departure, negative value indicates the flight departs before scheduled time Arrival_Delay, Numeric, Total delay on arrival, it is derived from the difference of arrival_time and scheduled_arrival, negative value indicates the flight arrived before scheduled time. Diverted,Numeric (binary data), Aircraft landed on airport that out of schedule Cancelled, Numeric (binary data), 1 means cancelled Cancellation_Reason, String, Reason for Cancellation of flight: A - Airline/Carrier; B - Weather; C - National Air System; D - Security Air_System_Delay, String, Delay caused by air system Security_Delay, String, Delay caused by security Airline_Delay, String, Delay caused by airline Late_Aircraft_Delay, String, Delay caused by aircraft Weather_Delay, String, Delay caused by weather	This data is used as the major source of information in our project. We mainly use this data to analyse flight delays and reasons of delay. In addition, the data will be used investigate airport network and analyse airport network relationship by different centrality measures, such as betweenness centrality, degree centrality.

Background Survey of Related Work

Related Works	What We Can Learn
Monthly Performance of Airline in Asia Pacific Source: https://www.flightstats.com/company/monthly-performance-reports/airlines/	The heatmap provides a clear annotation from which viewers know the size stands for the scheduled flights whereas color for on-time performance. The colors are well contrast with each other
Trends in the Causes of Flight Delay in US Source: https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/2012_04_13.pdf	The use of line chart is effective in comparing the various delay causes The chart title is clear enough to demonstrate the chart purpose
Global Digital Attack Network Source: http://www.digitalattackmap.com/#anim=1&color=0&country=US&list=0&time=17475&view=map	The graph vividly displays the path with its origin and destination When mouse hovers on the path, the label shows up with its detailed information

PROPOSED STORYBOARD

Proposed Layout	How Analyst Can Conduct Analysis
	Introduce analysts to the topic of HDB Resale Price and the objectives of the visualization project Upon clicking "Find your Dream Home", analysts will then begin their process of exploration
	When a user enters our app, we will show them a brief history of HDB followed by the problem that most young people are facing with regards to understanding the HDB situation. The 2 screens of different insights we are trying to show will be displayed as 2 clickable buttons so that it is easy for a user to know what exactly he wants to look for at a glance. The dual axis bar-line chart will indicate the number of units sold vs the HDB price index to show the performing over the years. The scatter plot groups attacks based on 3 main categories - Planning Area, HDB resale price, Life left on lease. Firstly, by grouping based on planning area, it shows the the different HDB of how many years they left on lease. The size of the circle indicate the resale price of the HDB
	In the next phase of the exploration, we The radar chart shows 5 different governance indicators that defines how well a HDB is price with several other indicators. The closer the area is to the center of the chart, the less well the indicators is. Upon mouse-over of each area, one can also retrieve the exact values of each governance indicator. Using the map of Singapore as a filter condition, analysts can selected their choice of HDB to see if its near any bus stop, MRT, schools. By looking at both charts, the analyst will then be able to compare and establish possible linkages between the different indicators for HDB over the years. As such, these 2 charts are placed side by side to assist the analyst in their data exploration.

Technical Complexity

Below are the list of technical challenges that team may be faced with when developing the visualization application.

Technical Challenges	How To Resolve
Unfamiliar with D3.js libraries and building D3 application	Attend D3.js workshop Individual learning on how to build D3 application Peer Learning
Lack of knowledge on how to integrate tableau work with D3 application	Research on how to integrate tableau work with D3 application Conduct early integration so that team have enough time to tackle some potential errors.
Insufficient metadata for the source data	Research in the official website of US Department of Transportation Arrange team discussion to facilitate the understanding for the source data

Tools/Technology

Below are the tools/technologies we will use when developing the visualization

• Excel
• Tableau
• D3.js
• Gephi
  

Project Milestones