Group02 Proposal

PROPOSAL

POSTER

APPLICATION

RESEARCH PAPER

ALL PROJECTS

Overview

From the simplest forms of bartering that has been interwoven into the earliest fabric of human history, to the modern-day commodity derivatives traded on virtual exchanges, trade has always been an essential economic activity to mankind. Over the years, globalization has created complex inter-dependencies between countries.

Recent US’s announcement of the imposition of hefty tariffs on steel and aluminium on most countries as part of their economic policy has shattered the delicate balance of world trade. The breakout of a full-blown global trade-war seems to loom ahead, and amongst many questions that arise out of this possibility, we seek to apply visual analytics method to facilitate and share understanding on the “Casualties-of-War”.

Motivations and Objectives

Based on the Global Commodity Trade Statistics published by the United Nations Statistics Division, we have identified investable and tradable commodities which fall into Metals (such as gold, silver, platinum and copper), Energy (such as crude oil, heating oil, natural gas and gasoline), Livestock and Meat (including lean hogs, pork bellies, live cattle and feeder cattle) and Agricultural (including corn, soybeans, wheat, rice, cocoa, coffee, cotton and sugar). [1]

Our project aims to identify trends and patterns in international trade at geographic, regional and economic communities and to explore the trade dependencies among these countries. We also aim to explore the major importers and exporters of trade communities and to find out the relationships in Amount, Quantity and Volume of Trade. Our team is motivated to design a dynamic and interactive dashboard to provide policymakers a better understanding and holistic view of the international trade.

Through out analysis, we hope to address the following:

1) Commodity Trade Overview: Exploratory Analysis of International Trade by Trading Parameters
We want to explore the hierarchical relationships between trade balance, quantity and volume by trading parameters such as commodity type, trade flow and regions to identify interesting patters between 2007 to 2016.
Visualizations: Sunburst, Treemap, Sankey and Choropleth

2) Commodity Trade Diversification: Analysis of Trade dependencies by Regions
We would like to analyze trends and trade dependencies among geographical and economic groups such as Organization for Economic and Development (OECD), European Union (EU) and Southeast Asia (SEA) by the different commodity types and trade flow.
Visualizations: Time-series with geographic panels

Data Sources

The Global Commodity Trade Statistics data [2] is retrieved from United Nations Statistics Division of the UNData website. The retrieved 2.94 million rows of data between 2007 to 2016 comprises the following information:

Dataset

Variable Description

Global Commodity Trade Statistics

Country name of record Year in which the trade occured Harmonized Commodity Description and Coding System (HS) by World Customs Organization comprising about 5000 commodity groups; each identified by a six digit code Commodity category Description of a particular commodity code Flow of Trade (Import, Export etc.) Value of Trade in USD Bn Quantity count of a given item based on the Quantity Name Quantity measurement type based on the commodity type Description of the quantity measurement type

Tools & Packages

Dashboard and Data Manipulation

• shinydashboard
• DT
• data.table
• dplyr
• tidyverse

Visualizations

• sunburstR
• treemap
• networkD3
• geofacet
• ggplot2

References

Banner: https://www.drugdetectingdogs.com/detecting-dogs/miami/sweeper-florida/shipping/sniffing
[1] Commodities Trading: Overview. https://www.investopedia.com/investing/commodities-trading-overview
[2] Global Commodity Trade Statistics Data: United Nations Statistics Division. http://data.un.org/Explorer.aspx