Sixes: Proposal Version 1

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Proposal

Poster

Application

Research Paper

PROBLEM & MOTIVATION

About 275 million people worldwide, which is roughly 5.6 per cent of the global population aged 15-64 years, used drugs at least once during 2016. Some 31 million of people who use drugs suffer from drug use disorders, meaning that their drug use is harmful to the point where they may need treatment. The consequences of illicit drug use are widespread, causing permanent physical and emotional damage to users and negatively impacting their families, coworkers, and many others with whom they have contact. Our aim is that users can do better drug use prevention, treatment and care with visual analytics on the use of drug.

OBJECTIVES

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

1. View the geographical distribution of drug use in 2016
2. Identify which drug types that people are most addicted
3. The distribution of drug users' age groups

SELECTED DATASET

Datasets are retrieved from https://data.unodc.org/#state:1
The data set describes the annual prevalence of use of drug in 2016:

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

WIP

Proposed Layout	How Analyst Can Conduct Analysis

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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