Project Groups

ISSS608 Visual Analytics and Applications

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Visual Analytics Project

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Project Groups

Please change Your Team name to your project topic and change student name to your own name

Project Team	Project Title/Description	Project Artifacts	Project Member
Group 1	Gender Studies: A web-based analytics application for visualizing World Development Indicators As countries start to develop, more attention on Social Economic factors begin to be discusses in greater detail. In fact, the discussion of Social Economics may be deemed as a privilege of Developed countries, as developing countries continue to battle more fundamental economic factors like Gross Domestic Product, Population Growth, Education and so on. Social Economics, as defined, is the study of social phenomenons that make up the society at large. These include topics of discussions, a few of which are listed below: Lesbian Gay Bisexual Transsexual Rights Racial Discrimination Feminism and Women Equality Freedom Religious/Personal practice For our project, we would be focusing on Feminism and Women Equality. in line with the topic, there are many controversial topics of discussions. Such include the Gender Pay Gap, the Patriarchy, Abortion (Women's health care rights), etc, with the liberal impression that Women in developed countries are still suppressed into sub-leading roles, and that society is inherently "male" dominant. Our group hopes to dispel this theory with factual statistics, and as such, change the mindsets of women to "break" out of the "self-victimization" mentality, which has been recognized by groups of Conservative Physiologist as the stumbling block to Gender equality and progression.	Proposal Poster Application Report	GE Bin Ryan CHIA Danny LIM
Group 2	Environmental Criminology: The Missing "W" in Whodunnit Environmental Criminology, an approach first developed in the 1980s, involves the study of geospatial and contextual elements in relation to crime. These elements could involve aspects such as victim movement, and spatial-temporal patterns in the occurrence of crimes. Through the exploration of a crime record dataset provided by the Los Angeles Poice Department (LAPD), this project aims to provide a layman's view of criminology through the lens of geospatial-themed and statistical visual analytics. <motivation> <features>	Proposal Report [<Shiny App link>] Poster	Matilda Tan Ying Xuan Nurul Asyikeen Binte Azhar Rachel Tong
Group 4: A tale of Bitcoin	Ever wonder how far bitcoin value could go? Bitcoin has recently garnered mixed reviews from two extreme ends. From China banning bitcoin to Chicago Mercantile Exchange supporting the futures trading of bitcoin. And there are plenty more views from big investment banks as well as regulators. All these recent excitement is due to bitcoin’s value rising more than 700% since the start of January 2017. It is very tempting to speculate that the price will continue to go up. If it does, by how much? If it doesn’t, how hard will it fall? How is the relative performance compared to other instruments? There are many more questions from both investors and curious academics alike. This paper seeks to answer some of these questions through visualisation techniques by employing the R technology. In this project, we will perform limited technical analysis, time series analysis and return analysis through the usage of R. There are various packages which proof useful when it comes to quick data crunching and visually pleasing presentation. The data what we will be using is per minute close bitcoin price since 2009. Apart from price, we will also be comparing price information of indexes and other commonly traded commodities as a return comparison against bitcoin.	Proposal	DENG Yuetong YAU Hon Tak
Group 5	How civil aviation contributes to the “Belt and Road” initiative? The Belt and Road (B&R) refers to the land-based "Silk Road Economic Belt" and the seagoing "21st Century Maritime Silk Road". The routes cover more than 60 countries and regions from Asia to Europe via Southeast Asia, South Asia, Central Asia, West Asia and the Middle East. The B&R countries currently accounting for around 31% of global GDP and more than 34% of the world's merchandise trade. Unveiled in 2013, the strategy underlines China's push to take a larger role in global affairs with a China-centered trading network. The Belt and Road initiative is set to reinvigorate the seamless flow of capital, goods and services between Asia and the rest of the world, by promoting further market integration and forging new ties among communities. The main purpose of this project is to investigate the flight network between China and the “Belt and Road” countries to explore the economic connectivity and development potential. A visual exploration tool will be implemented using R shiny which can be used to easily explore and understand the flight network.	Proposal Poster Application Report	Wang Rui Wu Yuqing Xing Siyuan
Group 6: How Is Beijing Today?	Use the air quality indicators to save us On Nov 4th, Beijing Environmental Protection Agency released the news, owing to the adverse weather conditions and early winter heating as well as other factors, it is expected that there will be a continuous 4-day regional heavily polluted air quality in Beijing-Tianjin-Hebei and surrounding areas on November 4th, in addition, the air quality in some cities may reach serious pollution level…. “Why is China’s smog so bad now?”, a lot of people from overseas want to explore. With the rapid development of economy in China, news from China is more frequently commented in the globe. China’s air pollution has been a serious issue for more than 10 years, with the problem appealing more attention worldwide, the Chinese government has make big efforts to solve it. Beijing, one of the most serious polluted city, which is also the capital of China. Along with the escalation of air pollution, most people who are working and living in Beijing are faced with the tracheitis, pneumoconiosis, asthma, to name just a few. Gradually, a lot of people are terrified with living and working in Beijing. In our project, we mean to apply the tools and better visualize the changes of air quality according its existing indicators. We will show the historical AQI, the pollutant concentrations and trend charts by pollutants, forecast the further air quality in the different view point in Beijing. We hope that we can try our best to show the weather condition in hand and assist people in keep them in good health.	Proposal Poster RShinyApp Report	Wang Yizhou Zhou Chen Zhang Lidan
Group 8	Singapore CPI Index: A Detalied Data Analysis The Consumer Price Index (CPI) is an economic measure that reflects the prices of consumer goods and services a country's citizens consume for day to day living. Understanding it gives a clear overview of how the country’s standard of living is and its short-term forecasts can have deep ramifications. It is often used for tuning Governmental policies to steer inflation rates in Singapore, for potential migrants to assess the country’s living patterns, and for foreign investors to consider allocating potential investment funds into the country. However, to merely glance at the present CPI values provide limited information and its real value lies in its forecast. Given the myriad possibilities of how the market forces work, the CPI can be difficult to predict, especially in the long term. Analysts who are interested in the country’s growth and outlook would need to apply many variations of parameters to find the forecast that is nearest to its future realization. To tackle this difficulty, we propose to create an easy-to-use system that is assessible even to the uninitiated analyst. The system should allow exploratory functions to decompose the CPI time series data to its constituent parts, namely Seasonality, Trend, and Random (Noise). It should also generate several potential forecasting models (such as Exponential Smoothing and ARIMA) to predict the CPI using a combination of predetermined parameters and grid search optimization. The system will be programmed using the R Shiny package, and several useful supportive packages such as: Lubridate and Timetk (for date-time data manipulation), Forecast and Sweep (for easy forecasting), and ggplot2 (for amazing time-series visualizations). To extend our system further, we also allow other forms of time series data to be displayed and their forecasts compared using the given forecasting methods. Other example time-series data sources that are supported could include Singapore import/export prices, currency exchange rate information with other countries, and even Singapore Certificate-of-Entitlement (COE) price changes.	Proposal Poster Application Report	Fam Guo Teng Wang Yuchen Xu Yanru
Group 10	China property analysis The real-estate market is ever growing and has more stakeholders. We are here to build an app that makes an analysis of the housing prices market an easy and effective one by just a few clicks and hovering around. This way allowing the major stakeholders perform their analysis and plan their decisions more efficiently. We have used various packages such as'Recharts','Timekt','Sweep' that allowed users to model and visualize the housing prices indexes in different ways for different purposes. Time Series Analysis-The application will allow the user to choose the City they are interested in and the time period they want to look at. The trend of the prices during that period will be provided.This is built for analysts and agents and government officials who would like to know on the performance at a certain period of time and also a comparative study between different cities. This way they can find any outliers or a particular pattern in the indices. The time series is related to the economic policy and the effect is stressed based on the chosen policy time period. Cluster Analysis – We further develop some clusters of the cities based on their housing index reaction. This way we can group the cities whose housing market behave/ respond to the market in a similar way. The government officials and the local agents understand the markets better and plan their policies better. A waiver or cluster development centric policy can be made by the government. Forcast Analysis: Forecast analysis is done using Geofacet that we can compare the forecasted prices between the different region of the country. Geofaceting arranges a sequence of plots of data for different geographical entities into a grid that strives to preserve some of the original geographical orientation of the entities. This app can be applied to any other economic variable in China. This will be greatly helpful for economists, agents and government officials to look into the specific data and make some judgments and decisions based on it.	Proposal Poster Application Report	Aishwarya MOHAN Deng Chunling Ma xiaoliu
Group 12	Cross Shareholding Cross shareholding is a situation in which a corporation owns stock in another company. So, technically, corporations own securities issued by other corporations. Cross shareholding can lead to double counting, whereby the equity of each company is counted twice when determining value. When double counting occurs, the security's value is counted twice, which can result in estimating the wrong value of the two companies. Cross shareholding is very common in corporate world. Sometimes, there can be more than 10 companies involved and it is very difficult for investors and regulators to track who owns how much. In this project, our group choose 1 or 2 big groups of companies from Korea and China with heavy cross shareholding between each other and conduct visualization and relationship analysis on their networks using R-Shiny so that people can have better picture of these companies’ network and easier to understand relationship between companies.	Proposal Poster Application Report	KYONG HWAN KIM GONGQIANG HE ZIWEN
Team Members Group 1 GE BIN LIM LIANG DANNY RYAN CHIA Group 2 Rachel Tong Nurul Asyikeen Binte Azhar Matilda Tan Ying Xuan Group 3 CHEN ZHENGJIAN XIAO ZHENYU ZHENG MIANYI Group 4 Yau Hon Tak Deng Yuetong Group 5 Wang Rui Wu Yuqing Xing Siyuan Group 6 Wang Yizhou Zhou Chen Zhang Lidan Group 7 Zhang Peng Wang Shang Group 8 Fam Guo Teng Wang Yuchen Xu Yanru Group 10 Ma Xiaoliu Deng Chunling AISHWARYA MOHAN Group 11 FOO CELONG RAYMOND GOH JUN JIE ANTHONY KARAN JYOTI KHANNA Group 12 HE ZIWEN GONGQIANG KYONG HWAN KIM