Sixes: Proposal Version 1

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Research Paper

PROBLEM & MOTIVATION

Every year, more than 480,000 people die due to tobacco-related diseases. That is around 1 in 5 of all deaths annually. It is estimated that 1 in 2 smokers will die from a smoking-related disease. This interactive data visualization tool shows modeled trends in smoking prevalence worldwide. Our aim is to reveal perspectives of smoking and correlates, determinants and consequences about smoking with visual analytics.

OBJECTIVES

In this project, we are interested to create a visualisation that helps users perform the following:

1. View the geographical distribution of smokers from recent years
2. Share of perniciousness attributed to smoking
3. Reveal the trends of smoking and other perniciousness attributed to smoking of specific area or countries, while compared to worldwide value, to bring to attentions for both individuals and countries.

SELECTED DATASET

The dataset for analysis will be retrieved from multiple databases, as elaborated below:

Dataset/Source	Data Attributes	Rationale Of Usage
Consumption of tobacco products, prevalence of smoking and mortality (http://www.pnlee.co.uk/imass.htm)	Country name Country code Consumption Year Prevalence	To evaluate the daily smoke consumption for every country at specific year To evaluate the prevalence for every country at specific year Analyze the trend
Death rates and absolute number of premature deaths from smoking and secondhand-smoke (http://ghdx.healthdata.org/gbd-results-tool)	Country name Country code ISO Country code Daily smoker death Year	Group all countries by area to help analying the smoking situation and trend in each area Daily smoker and death data are prepared to derive the percentage of smoking death amoung smokers by country and year Analyze the trend of percentage of people who die due to smoking

BACKGROUND SURVEY OF RELATED WORKS

There are many charts and visualisations available which illustrates the various trends of house prices and index. We have selected a few of these to study and learn before we begin developing our own visualizations.

Related Works	What We Can Learn
https://dataunodc.un.org/drugs/prevalence_map	Heatmap is an explicit way to show the goegraphical distribution of data. The breakdowns shown upon hover give further details without distracting the audience at the first glance.
Map of annual seizures https://dataunodc.un.org/drugs/seizures_map%7C	Filter is essential to hide unnecessary data when only a group of data is focused.

PROPOSED STORYBOARD

Proposed Layout	What can we Analyse
	The navigation bar on top of the screen gives the entrances of the two visualisation sub-parts. Analysts will begin the process of investigation once they click map or data
	There are two filters to change the category and region displayed on the map The legend on bottom is to differentiate the concentration of the population of a specific category. The slider is to autoplay the changes of the map across the years.
	Upon clicking an individual country on the map, the dialog will be shown. The diagram is to show the comparasion between the country and the global situation. Upon hovering on one data point on the diagram, the detail comparasion data including the world rank is displayed.
	Upon clicking an individual concentration level on the legend, the dialog will be shown. This dialog provides a vertical comparasion among the countries within the same concentration level. The inner circle is the corresponding continent, while the outer circle is the countries belonging to the continent.

KEY TECHNICAL CHALLENGES

The following are some of the key technical challenges that we may face throughout the course of the project:

Key Technical Challenges	How We Propose To Resolve
Unfamiliarity of Visualization Tool Usage	Independent Learning on Visualization Tools Peer Learning
New to R and Javascript	Attend R Workshop Self explore on R & Technical Tools Peer Learning
Data Cleaning & Transformation	Work together to clean, transform and analyze the data Documentation to keep track of changes

PROJECT TIMELINE

The following shows our project timeline for the completion of this project:

TOOLS/TECHNOLOGIES

The following are some of the tools/technologies that we will be utilizing during the project:

• Excel
• Github
• Tableau
• R

WIP

REFERENCES

• https://data.unodc.org/

WIP

COMMENTS

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