Difference between revisions of "Group02 Proposal"
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=Motivations and Objectives= | =Motivations and Objectives= | ||
| − | + | There is motivation to provide novel visual insights on a current and complex matter that affects the entire world. Using Global Commodity Trade Statistics published by the United Nations Statistics Division, we have identified investable and tradable commodities which fall into Metals, Energy, Livestock & Meat and Agricultural [1]. Integrating the Commodity Trade with the current GDP data from the World Bank, we plan to identify trends, patterns and dependencies in commodity trade at geographic, regional and economic communities; and identify economies that are sensitive to trade, along with the particular commodities that give rise to this sensitivity. We use a funnel methodology by generalizing our data visualizations by geographic and financial trade commodity groupings before providing a drill-drown facility in an interactive dashboard to help policymakers have a better understanding their economies and trade given the looming trade-war. | |
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Through out analysis, we hope to address the following: <br> | Through out analysis, we hope to address the following: <br> | ||
Revision as of 09:45, 29 November 2018
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Overview
Empires rise and fall because of it; its ways are looked upon as the lifelines for nations who fought and died for it. Yet, it is something that you engage in as part of your daily life. 'It' refers to trade, which is the exchange of goods and services, often with compensation paid by the buyer to the seller.
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
There is motivation to provide novel visual insights on a current and complex matter that affects the entire world. Using Global Commodity Trade Statistics published by the United Nations Statistics Division, we have identified investable and tradable commodities which fall into Metals, Energy, Livestock & Meat and Agricultural [1]. Integrating the Commodity Trade with the current GDP data from the World Bank, we plan to identify trends, patterns and dependencies in commodity trade at geographic, regional and economic communities; and identify economies that are sensitive to trade, along with the particular commodities that give rise to this sensitivity. We use a funnel methodology by generalizing our data visualizations by geographic and financial trade commodity groupings before providing a drill-drown facility in an interactive dashboard to help policymakers have a better understanding their economies and trade given the looming trade-war.
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 |
|
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
