Difference between revisions of "Project Groups"

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[[Group01_Overview|Group 1: The Three Musketeers]]<br><br>[[File:grp01_headerImage.png|209px|center]]
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[[GroupXX_Overview|GroupXX: By default this is your group number. Feel free to give a name for your group]]
 
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'''World Development Indicators: A New Visual Perspective'''<br>
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'''Project title: Provide eyes catching title.  However, it should reflect the content or/and the focus of your project'''<br>
''A web-based analytics application to visualize countries development across the globe''
 
  
World Development Indicators (WDI) is an extensive and holistic database compiled by World Bank focusing on countries development across the globe. It covers 20 topics with more than 1,300 time series development indicators featuring 214 nations and 38 country group which adds up to more than 7 million data points collected over the span of 56 years.
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'''''Abstract'''''
  
The massive amount of world development data has by far exceeds the ability for students, policymakers, analysts and officials to transform the data into proper visualization for analysing and gaining insight of the global developmental landscape. Thus, creating an adverse impact on the financial and technical assistance World Bank is providing to the developing countries around the world.
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''The abstract should not be more than 350 words.''
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*[[GroupXX_Proposal|Proposal]]
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*[[GroupXX_Poster|Poster]]
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*[[GroupXX_Application|Application]]
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*[[GroupXX_Report|Report]]
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||
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* Member 1
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* Member 2
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* Member 3
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|-
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<div style="text-align:center;">
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[[File:cybersec2.png|230px]]
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</div>
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'''Cyber-security: you are in more danger than you can possibly imagine'''<br>
 +
 
 +
'''''<small>Cyber-attacks are becoming increasingly sophisticated. Coupled with the growing amount of data being generated by individuals, corporations and governments, well-orchestrated attacks could potentially cause major disruptions to any country, such as gaining access to national defense systems. According to David Koh, CEO of Singapore’s Cyber Security Agency, Singaporeans are largely aware of cybersecurity threats but do not take the necessary precautions, which may be due to complacency stemming from Singapore's reputation as a safe country<sup>1</sup>. Hence, public education is still required to urge individuals into taking preventive measures. This project will contribute to that end by providing interactive and interesting visulisations of cyber-attacks that can engage members of the public.</small>
 +
 
 +
<sup>1</sup>https://govinsider.asia/innovation/cyber-war-csa-singapore-david-koh/
 +
 
 +
'''''
  
To address this pressing issue, the team is motivated to design and develop a single-view, dynamic and interactive visual dashboard to provide students, policymakers, analysts and officials a holistic view of the World Development Indicators data collected.
 
 
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*[[Group01_Proposal|Proposal]]
 
*[[Group01_Proposal|Proposal]]
 
*[[Group01_Poster|Poster]]
 
*[[Group01_Poster|Poster]]
*[https://angad-sr.shinyapps.io/isss608-group_2-grit/ Application]
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*[[Group01_Application|Application]]
 
*[[Group01_Report|Report]]
 
*[[Group01_Report|Report]]
 
||
 
||
* GE Bin
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* Lim Yee Cheng
* Ryan CHIA
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* See Kwan Yen
* Danny LIM
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* Zheng Weijie Jay
 +
|-
 +
 
 +
||
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<div style="File:center;">
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[[File:Group2_logo1.jpg|frameless|center|250px|link=https://wiki.smu.edu.sg/1718t3isss608/Proposal]]
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</div>
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 +
'''World Energy Production & Consumption:<br> A Visual Study'''<br>
 +
 
 +
For 66 years, the BP Statistical Review of World Energy has provided high-quality objective and globally consistent data on world energy markets. The review is one of the most widely respected and authoritative publications in the field of energy economics, used for reference by the media, academia, world governments and energy companies. A new edition is published every June.<br><br>
 +
 
 +
Join us as we explore the rich data-set provided by BP & study the dynamics of regional energy production and consumption of the different countries of the world to identify the dominant as well as weaker player in the world energy market.
 +
 
 +
||
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*[[Group02_Proposal|Proposal]]
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*[[Group02_Poster|Poster]]
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*[[Group02_Application|Application]]
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*[[Group02_Report|Report]]
 +
||
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* Aakanksha Kumari
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* Amrutha Rajeshwari Yejerla
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* Priyanka Sharma
 
|-
 
|-
 +
 
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<div style="text-align:center;">
 
<div style="text-align:center;">
[[Group_2_Overview|Group 2:Exploring Associations of Geospatial-temporal Factors - A Visual Interactive Toolkit]]<br><br>[[File:Kernel Density.png|209px|center]]
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[[File:CPITitle.jpg|350px|alt text = "Group 03"|link="https://wiki.smu.edu.sg/1718t3isss608/Group03_Proposal"]]
 
</div>
 
</div>
 
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'''Environmental Criminology: The Missing "W" in Whodunnit'''
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'''Perceiving Evil: The Study of the Corruption Perception Index'''<br />
 +
 
  
With increased availability of crime data rich with geospatial-temporal variables, exploratory, statistical and predictive analytics can be leveraged on to understand crime occurences with the lens of environmental criminology. The application produced from this research leverages on previous works on analysing interaction and associations amongst crime data variables that is supplemented with the population data. With Los Angeles city crimes used as our case study, we demonstrate how results from various analytical methods can be displayed visually and intuitively for exploration by the casual user with interactivity catered to potential varying needs. In particular, the application displayed exploratory and predictive statistcal analytics results using radar charts, calendar plot, choropleths, small multiples of choropleths, multimodal network graphs, heat maps and geographical maps.  
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First launched in 1995, the Corruption Perceptions Index (CPI) has been widely credited with putting the issue of corruption on the forefront of the international policy agenda. It score countries on how corrupt their public sectors are seen to be. By marrying the data set from Transparency International on their CPI records through the years versus the World Bank data set, which contains World Development Indicators (WDI) of the same countries, we will try to find out if there is indeed any correlations between the perceived corruption level of a country, and its actual conditions.  
  
 +
Is it true that a corrupted country is naturally poor? Are GDP growth linked with corruption? Does the gender composition of the country affects corruption? We will try to find out here.
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*[[Group03_Proposal|Proposal]]
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*[[Group03_Poster|Poster]]
 +
*[[Group03_Application|Application]]
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*[[Group03_Report|Report]]
 
||
 
||
*[[Grp2_Proposal|Proposal]]
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* Jan Patrick Mabilangan Gosioco
*[[Group02_Report|Report]]
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* Winston Lim Wee Kiong
*[https://rchlt.shinyapps.io/va-g2-lightapp/ Light Version of App^]
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* Yeo Kaijun
*[https://tinyurl.com/yaapkvx7/ Code for full-scale App]
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|-
*[https://tinyurl.com/ybmxe3d8/ Data for full-scale App]
 
*[[Group02_Poster|Poster]]
 
  
^ Light Version contains 10 months of data (Jan, Feb, Aug, Sep, Dec for 2016 and 2017)
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<div style="text-align:center;">
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[[File:ISSS608_Group4_Icon.png|frameless|center|375px|link=https://wiki.smu.edu.sg/1718t3isss608/Group04_Overview]]
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</div>
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'''Water For Life: Effect Of Rainfall On India's Crop Productivity'''<br />
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'''''
 +
Climate change has a serious impact on the availability of various resources on the earth especially water, which sustains life on this planet. One occupation that has experienced a direct impact due to these increasing climate fluctuations is <b><i>Agriculture</i></b>. Especially in a country like India where water, the most critical agricultural input is scarce. Nearly 55% of the total cultivated areas in India do not have irrigation facilities. And hence Indian farmers are highly dependent on rainfall as rainfall is the fundamental driver of water availability for agriculture. Changes in precipitation affect the quality and quantity of the agriculture produce in direct proportions of the rainfall received.
  
 +
In this study, we intend to analyse India’s rainfall pattern for past few years using various exploratory techniques, primarily focusing on apt visualizations to reveal the undiscovered truth. Over 80% of the annual rainfall is received in the four rainy months of June to September. There is great regional and temporal variation in the distribution of rainfall and although the monsoons affect most parts of India, the amount of rainfall varies from heavy to scanty on different parts. The primary motive of our analysis is to scrutinize the effect of irregularities in the rainfall pattern on agricultural productivity in India. Through our analysis, we would like to derive meaningful insights that foster our understanding about the most affected regions and crops because of the variability in climactic change so that actionable recommendations could be sought from the final developed application.
 +
'''''
 
||
 
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* Matilda Tan Ying Xuan
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*[[Group04_Proposal|Proposal]]
* Nurul Asyikeen Binte Azhar
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*[[Group04_Poster|Poster]]
* Rachel Tong
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*[[Group04_Application|Application]]
 +
*[[Group04_Report|Report]]
 +
||
 +
* Akanksha Shrirang Yadav
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* Jyoti Bukkapatil
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* Pooja Manohar Sawant
 
|-
 
|-
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<div style="File:center;">
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[[File:SM3.png|400px|link=https://wiki.smu.edu.sg/1718t3isss608/Social_Stratification_Mappers_Overview]]
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</div>
 
||
 
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[[Group_3_Overview|Group 3: Shiny-GWR Geovisual Analytics Application]]<br><br>[[File:Icont3.JPG|209px|center]]
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'''Exploring Inequality’s Geographic Dimension Across Neighbourhoods in Singapore: Its Driving Forces & Touch Points'''<br>
 +
 
 +
Amidst the recent debate over growing social inequality in Singapore such as the distinct clustering of elite schools and varying access to resources, the dangers of hardening social mobility pose as a concern for a culturally diverse nation that has upheld its values of social cohesion and racial harmony. In bridging social divide, Singapore has put in place various community programmes to create shared experiences and promote inter-communities mixing.
 +
 
 +
Using geospatial techniques in R, the dashboard serves to explore the geographic dimension of social inequality, by mapping the extent of social segregation and accessibility to important spaces across neighbourhoods. This is done in three approaches. First, we analyse whether there exists social segregation across subzones using the Entropy-Based Diversity Index, based on three dimensions of inequality - race, age and housing type. Second, using spatial point pattern analysis at the HDB postal code level, we visualise whether there exist housing type clusters that could point towards social inequality and whether certain towns are overpopulated with a specific housing type. Third, using the Hansen Accessibility Model, we map out available touch points that could facilitate social mixing, particularly the ease of access to primary schools. We also see whether there is any variation in accessibility between the elite and mainstream primary schools for different housing types. This is because an important aspect of social inequality is having reasonably fair access to resources. Lastly, we move into solutioning and explore whether there exist sufficient common spaces that allow for social mixing, such as parks, and identify areas that are underserved for urban planners to focus their attention on for future space planning.
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||
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*[[Social Stratification Mappers_Proposal|Proposal]]
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*[[Social Stratification Mappers_Poster|Poster]]
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*[[Social Stratification Mappers Project Application|Application]]
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*[[Social Stratification Mappers_Research Paper|Research Paper]]
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||
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* CHAN EN YING GRACE
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* LIU YUQING
 +
* LIU YUANJING
 +
|-
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<div style="text-align:center;">
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[[File:Buymore.png|260px|link=https://wiki.smu.edu.sg/1718t3isss608/Group06_Proposal]]
  
'''Building a geo-visualization application to analyse district economy in east region of China with geographically weighted regression (GWR) technique'''
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[[Group06_Overview|Group06]]
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</div>
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'''Buy More! – Maximizing Revenues'''<br>
  
Geospatial analysis was developed for problems in the environmental and life sciences, which has currently extended to almost all industries including economy, defence, utilities, social sciences, and public safety.  The application of geo-visualization using geographically weighted regression (GWR) is an exploratory technique mainly intended to indicate where non-stationarity is taking place on the map. It is a good exploratory analytical tool which creates a set of location based parameter estimates, able to be mapped and analysed to give spatial information for the relationship of explanatory variables and response variable.
+
Taking advantage of data is key to ensuring the survival of an e-commerce retail business. Through the visualization of the spending habits of customers and the visualization of the results from various machine learning algorithms, insights can be gathered as to which customers the retailer should target and what type of products should be kept in-stock to maximize sales.  
  
 +
An e-commerce company in the United Kingdom has provided their transaction data from 1 December 2010 to 9 December 2011. This company mainly has wholesalers as its customers. Based on the data provided, the company’s client portfolio is mainly based in the United Kingdom.
  
Our study uses economical data to explore district GDP condition in northern region of China. The project scope covers the analysis, model and visual representation of multivariate factors like GDP,Industry Output, Usual Residence,Average Wage,Area,City Construction Rate,No. of higher institution, and ratio of Teacher/Student which contributes to economical development in each city area of the province or municipality with the assistance of interactive charts and graphs.
+
On the market, there are various customer intelligence platforms available: “DataSift”, “SAS Customer Intelligence”, “Accenture Insights Platform”, etc. However, none of them are offer an integrated bespoke solution for our data on hand. Our motivation is to build an entirely bespoke application that would allow the company to fully analyse their data right at the onset and thus maximize the revenue of the company.
  
 
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||
*[[Group_3_Proposal|Proposal]]
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*[[Group06_Proposal|Proposal]]
*[[Group_3_Application|Application]]
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*[[Group06_Poster|Poster]]
*[[Group_3_Poster|Poster]]
+
*[[Group06_Application|Application]]
*[[Group_3_Report|Report]]
+
*[[Group06_Report|Report]]
 
||
 
||
* Xiao Zhenyu
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* ZHANG Yingdi
* Chen Zhengjian
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* FU Chuanjie
* Zheng Mianyi
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* WANG Runyu
 
|-
 
|-
 +
 
||
 
||
[[Group_4_Overview|Group 4: A tale of Bitcoin]]<br><br>[[File:Bitcoin.png|209px|center]]
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<div style="text-align:center;">
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[[Image:T7-MP.jpg|350px|frameless|center|link=https://wiki.smu.edu.sg/1718t3isss608/Group07_Proposal]]
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[[Group07_Overview|Group07]]
 +
</div>
 
||
 
||
 +
'''Singapore Property Market Watch - Your new tool to visualize SG Property Trend'''<br>
  
'''Ever wondered how far bitcoin's value could go?'''
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"Have your heard that Singapore IRAS just increased Additional Stamp Duty rate (ABSD)?! And US Federal Reserve will increase the interest-rate again?! How does Singapore Property market going to change now, we wanna see market trend leh, but how?"
  
Bitcoin has recently garnered mixed reviews from two extreme ends, from China banning bitcoin to Chicago Mercantile Exchange supporting the futures trading of bitcoin. There are even more varying opinions from big investment banks to regulators. All this recent excitement is due to bitcoin’s value rising by more than 700% (as of October 2017) from the start of 2017.  
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There is a deficiency of Market Watch tool for analysing the real estate market data as well as the trends properly. As it is very important to show the trendline cross different years and time, however, these data are still in table formats and the visualizations are quite basic, most of trends are illustrated statically, static graphs are not explanatory enough to show a full picture of changes, which sets barriers for readers from getting any useful insights and findings.
  
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 its relative performance compared to other instruments? There are many more questions from both investors as well as curious academics alike. This paper’s focus will be on the following:
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To better understand how the Real Estate market price moves cross different type of sales, property types and planning areas in the last 20+ years. Our team will provide an unbiased visualization tool for readers to understand and compare the Property Market pattern changing overtime.
  
# price movement patterns and trends; and
 
# the risk and return profile of bitcoin
 
  
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*[[Group07_Proposal|Proposal]]
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*[[Group07_Poster|Poster]]
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*[[Group07_Application|Application]]
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*[[Group07_Report|Report]]
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||
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* Fu Yi
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* Orkhan Hasanli
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* Tan Yong Ying, Joanne
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|-
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<div style="text-align:center;">
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[[File:team8.png|200px|link=https://wiki.smu.edu.sg/1718t3isss608/Group08_Proposal]]
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</div>
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'''Group 8:'''<br>
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'''Understanding gender equality from a visual perspective'''
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<br>
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<br>
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With the improvement of quality of life across the world, the argument for various freedoms and rights surface and turn to hotly debated topics especially in highly developed countries. One such agenda is the push for the empowerment of women, amongst the fight against other forms of discrimination.
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 +
Given the growing importance on this area, our project seeks to encapsulate existing data and present it visually in a simple, understandable manner, to help further efforts in driving the agenda. Using graphical techniques complemented with some level of statistical modelling in R, our dashboard will provide a view on changing patterns in key indicators relating to gender equality and women empowerment with time, as well as attempt to highlight important variables which aid the growth of such indicators.
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*[[Group08_Proposal|Proposal]]
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*[[Group08_Poster|Poster]]
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*[[Group08_Application|Application]]
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*[[Group08_Report|Report]]
 +
||
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* Low Zhi Wei
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* Shi Chen
 +
* Yi Xiaoqin
 +
|-
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<div style="text-align:center;">
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[[Group09_Overview|Group09 Heart]]<br>
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[[File:Icon.png|flameless|150px|150px|Group09|link=https://wiki.smu.edu.sg/1718t3isss608/Group09_Overview]]
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</div>
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'''Contagious diseases analysis in US'''<br>
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Healthcare and diseases are the major concerns over past centuries. The germ theory of disease in the 19th century led to cures for many infectious diseases, at the same time, public health measures developed as the rapid growth of cities required systematic sanitary measures. Although Researches of contagious diseases are abundant, they are still mystery for the public due to their exclusion to the specialists.
  
The approach taken to answering these question is through various visualisation techniques built in R.
 
  
 +
Recently, contagious diseases such as malaria, influenza A(H5N1) virus (avian flu) and severe acute respiratory syndrome(SARS) reach high epidemic proportions in some countries, especially for developing countries. Studying the patterns of contagious diseases still is significant for recent healthcare industry, moreover, it is not only the specialists’ mission, with the help of technology, even the public have the privileges to explore such patterns. Thus, we intend to apply visual analytics technique and graph theory to visualise historical records of seven contagious diseases: Smallpox, Rubella, Hepatitis, Measles, Polio, Mumps, Pertussis from US during year 1916 to 2010 and to visualise the relationships among these seven diseases and their symptoms. This project aims at 1) build a two-mode network and apply graph theory to visualize how contagious diseases are related to their symptoms; 2) visualise the historical records for finding patterns over these typical contagious diseases so that can apply the findings to other diseases.
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*[[Group09_Proposal|Proposal]]
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*[[Group09_Poster|Poster]]
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*[[Group09_Application|Application]]
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*[[Group09_Report|Report]]
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* Chen Runpu
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* Chen Yanchong
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* Yang Zhengyan
  
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|-
  
 
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*[[Group_4_Overview|Proposal]]
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<div style="text-align:center;">
*[[Group_4_Application|Application]]
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[[File:G10_logo.png|400px|link=https://wiki.smu.edu.sg/1718t3isss608/Group10_Overview]]
*[[Group_4_Poster|Poster]]
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</div>
*[[Group_4_Report|Report]]
 
 
||
 
||
* DENG Yuetong
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'''Hello Shiny! - Voice integrated Visual analytics'''<br>
* YAU Hon Tak
 
  
 +
Global migration flows: With the world shrinking by the day with technology and humans being more than ever ready to scale distances in quests to follow a career path or to escape political persecution and war or in search of better quality of life or to be closer to family or friends, Migration and the resulting ethnic and racial diversity are amongst the most emotive subjects in contemporary societies. In recent times, the political salience of migration has strongly increased due to uproar of natives and other factors. For origin societies, the departure of people raises concern about the 'brain drain' on the one hand. For receiving societies, the settlement of migrant groups and the formation of ethnic minorities can fundamentally change the social, cultural, economic dimensions and cause lack of resources for the natives.
  
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Using R’s geospatial and quadrant analysis techniques, we aimed to delve into the migrant numbers data over the years from country to country conjoined with the remittances according to the world bank by them to the origin locations. Migration and remittance numbers will be analysed grouping the locations on continent, region and socio-economic status scales to identify relations between the factors separating the dominating and the dominated societies. A balance model was applied to analyze the migration flows between countries of the same development level.
 +
 +
<b>The visualizations are linked between each other and wrapped on to an interactive application which can be controlled by user voice inputs, we will be using a Javascript library interfaced to R shiny to control the application’s select, filter and switch inputs.</b>
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 +
||
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*[[Group10_Proposal|Proposal]]
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*[[Group10_Poster|Poster]]
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*[[Group10_Application|Application]]
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*[[Group10_Analysis Report|Report]]
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||
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* Kaushik JAGANATHAN
 +
* Priyadarsan SHANKAR
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* SONG Xuejing
 
|-
 
|-
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<div style="text-align:center;">
 
<div style="text-align:center;">
[[ISSS608_2017-18_T1_Group5_Report|Group 5: Aviation Expansion]]<br><br>[[File:G5_pic.jpg|250px|center]]
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[[File:Group11title.png|200px|centre|link=https://wiki.smu.edu.sg/1718t3isss608/Group11_Overview]]
 
</div>
 
</div>
 
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'''Linking the globe: An Interactive Dashboard for Exploring Aviation Expansion Along the "Belt and Road"'''<br>
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'''New York City Crime Watch'''<br>
''How civil aviation contributes to the “Belt and Road” initiative?''<br>
+
 
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Crime is an act punishable by law that has been timeless is prevalent in every society. Crime activities are recorded for crime analysis which involves systematic analysis for identifying and analyzing patterns and trends in crime and disorder.
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 +
For our crime analysis, we have used the New York Police Department (NYPD) crime data for the which spans crimes records across the 5 boroughs of NYC. We aim to provide a visual tool to observe the crime patterns with respect to time and location. On doing this, the rate of crime can be analyzed and hence forecasted for law enforcement agencies can estimate the right number of resources to deploy.
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||
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*[[Group11_Proposal|Proposal]]
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*[[Group11_Poster|Poster]]
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*[[Group11_Application|Application]]
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*[[Group11_Report|Report]]
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||
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* Diya Naresh Rao
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* Nevil Bruno
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* Vishal Badrinarayanan
 +
|-
  
The Belt and Road (B&R) refers to the land-based "Silk Road Economic Belt" and the seagoing "21st Century Maritime Silk Road". Unveiled in 2013, the strategy underlines China's push to take a larger role in global affairs with a China-centered trading network by reinvigorating the seamless flow of capital, goods and services between Asia and the rest of the world. with aim of promoting further market integration and forging new ties among communities, 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.<br><br>
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<div style="text-align:center;">
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[[File:p.jpg|400px|link=https://wiki.smu.edu.sg/1718t3isss608/Group12_Overview]]
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</div>
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Group 12<br/>
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'''<b>[[Group12_Overview|Have the Nations really progressed?]] - Story from World Bank statistics</b><br/>'''
  
By investigating all air-routes and flights between China and the “Belt and Road” countries between 2013 and 2017, the main purpose of this project is to explore the growing trend, regional connectivity and development potential in this aviation network. <br><br>
+
<br/>
 +
For almost a hundred years, two measurements have been used to get a sense of how well a country is doing. One is GDP, the other is its unemployment rate. But when it comes to figuring out how well a country is serving its citizens; these two might not be the only metrics to gauge a nations collective progress. On estimates of social progress, poorer countries often outdo their wealthier counterparts.
 +
Social progress is not completely explained by economic variables like GDP data. It can show surprising relationships that help shape policy. One of the interesting ways these kinds of indexes are used is to see how countries have improved or declined – or just stayed the same. It can determine which countries get help with funding. And it may even be able to help predict the future.
  
A web-based visual analytics tool is implemented using R shiny with Leaflet package which can be used to easily explore and understand the flight network.
+
Through our visualizations, we seek to utilize existing data to derive meaningful insights over how various socioeconomic factors have had an impact on development of different nations. Using graphical techniques in R, our dashboard will feature analysis on key indicators relating to financial, educational, gender, health, industry & demographic as well as attempt to highlight important variables which aid their growth.
  
 
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*[[ISSS608_2017-18_T1_Group5_Proposal|Proposal]]
+
*[[Group12_Proposal|Proposal]]
*[[ISSS608_2017-18_T1_Group5_Report|Report]]
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*[[Group12_Poster|Poster]]
*[[ISSS608_2017-18_T1_Group5_Poster|Poster]]
+
*[[Group12_Application|Application]]
*[[ISSS608_2017-18_T1_Group5_Application|Application]]
+
*[[Group12_Report|Report]]
 
||
 
||
* Wang Rui
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* Sudhir Panda
* Wu Yuqing
+
* Lokesh Vairamuthu
* Xing Siyuan
+
* Sameer Panda
 
|-
 
|-
  
 +
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 +
<div style="text-align:center;">
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<!--[[Group13_Overview|Group13]]-->
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[[File:G13 Logo.jpg|200px|link=https://wiki.smu.edu.sg/1718t3isss608/Group13_Proposal]]
 +
</div>
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'''Man - KIND?'''<br>
 +
 +
The Organization for Economic Co-operation and Development is an intergovernmental economic organization with 37 member countries, founded in 1961 to stimulate economic progress and world trade. Most OECD members are high-income economies with a very high Human Development Index (HDI) and are regarded as developed countries. As of 2017, the OECD member states collectively comprised 62.2% of global nominal GDP (US$49.6 trillion) and 42.8% of global GDP ($54.2 trillion) at purchasing power parity.<br>
 +
<br>
 +
But has this economic progress come at a cost? <br>
 +
Is there a relation between the growth factors versus the environmental damage imposed by these nations? <br>
 +
Do the Emission, Green Energy, and Economic Growth Indicators have a story to tell? <br>
 +
What factors, if any, binds certain clusters of similar performing nations?<br>
 +
<br>
 +
Join us on our data visualisation expedition as we attempt to explore some facts based on a 10 years OECD data.
 +
 +
 +
||
 +
*[[Group13_Proposal|Proposal]]
 +
*[[Group13_Poster|Poster]]
 +
*[[Group13_Application|Application]]
 +
*[[Group13_Report|Report]]
 +
||
 +
* Harisingh Khedar
 +
* Kiriti Yelamanchali
 +
* Suhas Awasthi
 
|-
 
|-
 +
 
||
 
||
 
<div style="text-align:center;">
 
<div style="text-align:center;">
[[Group_6_Overview|Group 6: Beijing Air Quality]]<br><br>[[File: Air3.jpg|209px|center]]
+
[[File:Randy-tarampi-225537-unsplash.jpg|border|380px|centre|link=Group14_Proposal]]
 +
[[Group14_Overview|Group14]]
 
</div>
 
</div>
 
||
 
||
 +
'''Towards Greater Transparency for the Global Arms Trade'''<br>
 +
 +
The global arms trade has been a major concern as the international transfer of arms between states could lead to wars, crimes against humanity and contribute to serious violations of international human rights. The Stockholm International Peace Research Institute (SIPRI) collects data on arms transfers between regions and states aimed at increasing the fundamental understanding of the impact of arms transfers and to support policymaking. Based on the latest publication by SIPRI, a rising trend is observed in the volume of international transfers of major weapons, with the highest volume of arm transfers recorded between 2013 to 2017, since 1990.
  
'''How is Beijing Air Quality in 2017?'''
+
Our project aims to use interactive visualisation to identify the trends and patterns in the international arms transfers and to explore the arms trade dependencies between countries and regions. 
  
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….
 
  
 +
||
 +
*[[Group14_Proposal|Proposal]]
 +
*[[Group14_Poster|Poster]]
 +
*[[Group14_Application|Application]]
 +
*[[Group14_Report|Report]]
 +
||
 +
* Tong Wen Liang Samuel
 +
* Miko Tan Mei Jia
 +
* Kalai Selvi
 +
|-
 +
 +
||
 +
<div style="text-align:center;">
 +
[[File:osprey_logo.jpg|200px|centre|link=Group15_Proposal]]
 +
[[Group15_Proposal|Group15]]
 +
</div>
 +
||
 +
'''Bird, Where Art Thou?'''<br>
  
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.
+
Animal migration has long received much attention as a research topic in biology. Information about animal movement serves to allow us to understand animal behavior and their interactions with each other and the environment. In addition, it allows us to address environmental challenges such as climate and land use change.
  
 +
Understanding animal migration helps conservationists to conserve these animals through the protection of their habitats and their resources.
  
In our project, we make efforts to visualize and analyze Beijing air quality according to its main existing indicators, such as AQI, NO, SO2, CO, PM2.5, etc.. To better display the visualization results, we utilize R Shiny Dashboard to make the part of the page design. Then, through exerting the r package of ggplot2, we visualize the fluctuation of AQI and frequency of AQI level. Besides, we generate the spider chart which shows the severity of each pollutant by using fmsb this package. We also display raster map and geofacet line graphs for 8 main view points through using the packages of ggplot2, maptools, gstat, raster, geofacet.  
+
An interactive visual analytics approach would provide valuable insights to the scientific community on the migration of these animals.  
  
  
All in all, we hope that we can try our best to show the air quality, and make people clearly know more about the surroundings they are living in as well as raise public environmental awareness.
 
  
 
||
 
||
*[[Group06_Proposal|Proposal]]
+
*[[Group15_Proposal|Proposal]]
*[[Group06_Poster|Poster]]
+
*[[Group15_Poster|Poster]]
*[[RShinyApp]]
+
*[[Group15_Application|Application]]
*[[Group06_Report|Report]]
+
*[[Group15_Report|Report]]
 
||
 
||
* Wang Yizhou
+
* Chen, Pin-an
* Zhou Chen
+
* He Mengqi
* Zhang Lidan
+
* Ong Wah Jie
 
|-
 
|-
  
 +
||
 +
<br>
 +
[[File:VA-logo greens.png ‎|300px|centre|link=Group16_Proposal]]
 +
<br>
 +
||
 +
'''Urban Pulse —— Visualization on Beijing's Traffic'''
 +
<br>
 +
In Beijing, traffic problem is always a shared concern among citizens. As China urbanizes, more and more people flood into first-tier cities, which has caused severe traffic congestions. Beijing is obviously on the top congestion city list. With taxi trajectory data collected by Microsoft from over 10,000 taxis in Beijing, this case aims to uncover traffic patterns through static and dynamic visualization and combine these findings to city construction to discover possible reasons behind these patterns. More over, suggestions will be given for three parties: urban road planning optimization for government, efficient taxi resources arrangement for taxi companies, and travel advice for citizens in Beijing.
 +
<br>
 +
||
 +
*[[Group16_Proposal|Proposal]]
 +
*[[Group16_Poster|Poster]]
 +
*[[Group16_Application|Application]]
 +
*[[Group16_Report|Report]]
 +
||
 +
* ALEJANDRO LLORENS MORENO
 +
* JIANG YILIN
 +
* LI HONGXIN
 
|-
 
|-
 +
 
||
 
||
 
<div style="text-align:center;">
 
<div style="text-align:center;">
[[Group 7 Overview|Group 7: Bike Sharing]]<br><br>[[Image:Shareing_bicycle.png|250px|center]]
+
[[File:G17_vizNetwork_Logo.png||200px|centre|link=Group17_Overview]]
 +
[[Group17_Overview|Group17]]
 
</div>
 
</div>
 
||
 
||
 +
'''GeBiz: Who supplies to the needs of Singapore?'''<br>
  
'''Bike Sharing'''
+
Government Procurement is the procurement of goods and services on behalf of a public authority. As per policy, the procurements need to be done through an issue of public Tenders to prevent corruption, wastage, and local protectionism. GeBiz is the Singapore government's one stop portal for the above purpose. The data of past procurements are made available for the public in the Data.gov.sg portal. It is difficult to identify bias in such data available that have multiple transactions. Since a transaction involves various levels of the government, the bias may not be obvious while looking at the issuing authority and the supplier alone.
  
Pronto Cycle Share, branded as Pronto!, was a public bicycle sharing system in Seattle, Washington, that operated from 2014 to 2017. The system, owned initially by a non-profit and later by the Seattle Department of Transportation, included 58 stations in the city's central neighbourhoods and above 500 bicycles.
+
We propose an approach which combines network analysis, association analysis, and visual analytics to make this process easier. Traditionally, Association analysis has been used to identify relations between products purchased together. It is also applicable to any data that follows the format of multiple entities and a common transaction that links them together. In our case, the entities involved are the issuing agency and the supplier. The current visualizations treat all entities involved to be of the same category, thus making the visualization less intuitive. We want to come up with a visualization that can overcome this limitation.
  
Bike-sharing is a short distance transportation for people to make their life more convenient. When people use shared-bike, they can borrow and return bikes at any stations in the service station. Some stations have too many incoming bike and get jammed without enough docks for upcoming bikes, while some other stations get empty quickly and lack enough bikes for people to check out.
+
||
 +
*[[Group17_Proposal|Proposal]]
 +
*[[Group17_Poster|Poster]]
 +
*[[Group17_Application|Application]]
 +
*[[Group17_Report|Report]]
 +
||
 +
* Joel Choo Peng Yeow
 +
* Manu George Mathew
 +
* Minami Yusuke
 +
|-
  
'''Which station has the most passenger flow?'''
+
||
 +
<div style="text-align:center;">
 +
[[File:Crime_India_Logo.gif|300px||centre|link=https://wiki.smu.edu.sg/1718t3isss608/Group18_Overview]]
 +
</div>
 +
||
 +
'''A sanctuary for women – Is there one?'''<br>
  
In our project, we calculate the in degree an out degree for each station, to help user to understand how passenger usually use bike sharing service through each station point. We also divided time range into different periods, the data users can see much more details in yearly, monthly, even hourly. So that they can understand better the bike usage pattern.
+
Crime against women in India is very old social issue which is prevalent in almost all societies. It is increasing day by day and deeply rooted in the Indian society even after increasing education level of people. Inefficient legal system, weak rules of laws and patriarchal society in the second most populous country are few factors attributing and triggering increase in crime against women. The recent public outcry following a brutal gang rape of a young woman in India's national capital was a watershed moment in the world's largest democracy. The hype in the media across the world compels us to believe that crimes against women in India is on a dramatic rise.In our analysis, we take a step forward in this direction to discover the hidden truth in the Women Crime data using visualization techniques to better understand crime occurrences against women in India.
 +
||
 +
*[[Group18_Proposal|Proposal]]
 +
*[[Group18_Poster|Poster]]
 +
*[[Group18_Application|Application]]
 +
*[[Group18_Report|Report]]
 +
||
 +
* Alagu Alagappan
 +
* Rupini Sinnan Chettiar Pandian
 +
* Vigneshwar Vadivel
 +
|-
  
'''How to re-distribute bike at a lower cost?'''
+
||
 +
<div style="File:center;">
 +
[[File:Group19_Logo.jpg|250px|frameless|center|link=https://wiki.smu.edu.sg/1718t3isss608/Group19_Proposal]]
 +
</div>
 +
||
 +
'''Male or Female, that is a question!!'''<br>
  
Because passenger will take the bike from one station to another station everyday, Company should ask employees to re-distribute bike among existent stations. In our project, we use the real map, cooperated with the degree data calculated before, to visualize a shortest path to help employees re-distribute bike in a more efficient way.
+
Based on “The Global Gender Gap Report 2017”, China remains the world’s lowest ranked country with regard to the gender gap in its sex ratio at birth. Tracing back to previous census data and demographic statistics, sex ratio at birth in China has been on the high side since the early 1980s and rising continuously. In this project, We try to find out the socio-economic and cultural factors that leading to the increase of the sex ration at birth, which may be meaningful to curb the increase of birth sex ratio and restore it to normal level.
  
 
||
 
||
*[[G7 Project Introduction|Proposal]]
+
*[[Group19_Proposal|Proposal]]
*[[G7 Poster|Poster]]
+
*[[Group19_Poster|Poster]]
*[[G7 Application|Application]]
+
*[[Group19_Application|Application]]
*[[G7 Report|Report]]
+
*[[Group19_Report|Report]]
 
||
 
||
* Zhang Peng
+
* Bi, He
* Wang Shang
+
* Chen, NanNan
 +
* Teng, Fei
 
|-
 
|-
  
 +
||
 +
<div style="text-align:center;">
 +
[[File:Group_20.gif|350px|centre|link=Group20_Proposal]]
 +
[[Group20_Proposal|Group20]]
 +
</div>
 +
||
 +
'''[[Group20_Proposal|The air quality in China]]'''<br>
 +
<br/>
 +
Like other countries, China has to date followed a pattern of grow first, clean up later. Many developed cities have serious environment problems. Particularly, in 2015, Beijing had experienced heavy smog for 6 months and severe polluted days for more than 1 month. Everyone was talking about air quality and health. In recent years, government has put the green development in the first place, so dose our air quality become better?
 +
 +
To understand the improvement of air quality of developed cities and the impact of air quality on the health of residents, we choose four first-tier cities (Beijing, Shanghai, Shenzhen and Guangzhou) and 15 new first-tier cities (Chengdu, Hangzhou, Wuhan, Nanjing, Chongqing, Tianjin, Suzhou, Xian, Changsha, Shenyang, Qingdao, Zhengzhou, Dalian, Dongguan and Ningbo) to analyze.
 +
 +
||
 +
*[[Group20_Proposal|Proposal]]
 +
*[[Group20_Poster|Poster]]
 +
*[[Group20_Application|Application]]
 +
*[[Group20_Report|Report]]
 +
||
 +
* Chen Fan
 +
* Huang Yiyun
 +
* Xie Zhimao
 
|-
 
|-
 +
 
||
 
||
[[Group_8_Overview|Group 8: Time Series Explorer]]<br><br>[[File: Group8ProjectBanner.png|350px|center]]
+
<div style="text-align:center;">
 +
[[File:Hello1.jpg|300px|center]]
 +
[[Group21_Proposal|Group21]]
 +
</div>
 
||
 
||
'''Time-series Explorer: Building interactive data visualisation for time series analysis'''
+
'''MOVE TO WHAT MOVES YOU!'''<br>
  
Time-series analysis is a time and effort consuming endeavour. As budding data analysts, we spent considerable resources in experimenting with many variations of parameter configurations to analyse time-series data. This difficulty stems from the lack of automatic tools that can help calculate the optimized time-series parameters during model training. To tackle this challenge, we created an easy-to-use time-series exploration system that is accessible even to the uninitiated analyst. The system is able to decompose the time series data to its constituent parts, namely Seasonality, Trend and Random (Noise). It can generate several forecasting models, using Exponential Smoothing and ARIMA analysis techniques, to predict future time periods using optimization techniques. The system also allows other forms of time series data to be displayed and their forecasts compared using the given forecasting methods, within certain formats. To test the system capabilities, we adopted the Singapore Consumer Price Index (CPI) as our use case. The CPI, with its short-term forecasts, is often used for tuning Governmental policies to steer inflation rates in countries like Singapore and for foreign investors to consider allocating potential investment funds into the country.
+
With inflation in prices of land and an increase in human population, the Real Estate Market in Singapore has seen high volatility over the years. We observe that the market has significantly higher demand than supply, thereby creating a dilemma for people about the kind of property they should invest in. Our project is based on real estate sales data for 2017-2018 and provides transaction details, data on Flat Model, Flat Type, Lease and other relevant details. Through the scope of this project, we intend to provide a detailed understanding of the real estate market so that the users of the application can make a more informed decision. We believe that real estate agents and brokers, economists, investors and other enthusiasts can use the application to understand market trends and make investment decisions.
  
 
||
 
||
*[[Group_8_Overview|Proposal]]
+
*[[Group21_Proposal|Proposal]]
*[[Group_8_Poster|Poster]]
+
*[[Group21_Poster|Poster]]
*[[Group_8_Application|Application]]
+
*[[Group21_Application|Application]]
*[[Group_8_Report|Report]]
+
*[[Group21_Research_Paper|Report]]
 
||
 
||
* Fam Guo Teng
+
* Vaishnavi Agarwal
* Wang Yuchen
+
* Param Gadhaiya
* Xu Yanru
 
 
|-
 
|-
 +
 
||
 
||
[[Group10_Overview|Group 10:China Property Trend]]<br><br>[[File:Geocluster.jpeg|209px|center]]
+
<div style="text-align:center;">
 +
[[File:Kiva.png.jpg|230px|centre|link=Group22_Overview]]
 +
[[Group22_Proposal|Group22]]
 +
</div>
 
||
 
||
'''China property analysis'''
+
'''<big>Small loan, Big difference</big>'''<br>
  
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.
+
'''''Kiva is an international non-profit, founded in 2005 and based in San Francisco, with a mission to connect people through lending to alleviate poverty. Kiva celebrates and supports people looking to create a better future for themselves, their families and their communities. What we try to do is helping the website extend to more countries and helping more people solve the survival problems.'''''
  
We have used various packages such as'Recharts','Timekt','Sweep','ggplot2' that allowed users to model and visualize the housing prices indexes in different ways for different purposes.
+
||
 +
*[[Group22_Proposal|Proposal]]
 +
*[[Group22_Poster|Poster]]
 +
*[[Group22_Application|Application]]
 +
*[[Group22_Report|Report]]
 +
||
 +
* YU,ZHECHENG
 +
* GAO,JIAOYANG
 +
* MU,FUYAO
 +
|-
  
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.
+
||
 +
<div style="text-align:center;">
 +
[[File:Air_Pollution.jpg|350px|link=https://wiki.smu.edu.sg/1718t3isss608/Group23_Overview]]
 +
</div>
 +
||
 +
<big>'''MAKE THE WORLD A BETTER PLACE TO “BREATHE”'''</big>
  
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.
+
'''''
 +
Air pollution, as one of most fatal and yet invisible pollution in the world, is also one type of pollution we can’t escape from. It’s in the air we breath in and out and it’s causing threats to all living creatures on this planet. However, as research done by World Health Organization (WHO) shows, till 2016, the air pollution level has again, risen by 8%. Every nature sign urges for immediate actions upon improvements IN air quality, but HOW?
  
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.  
+
Our project aims to create a collaborative interface to track for everything that is happening in the world and to which extent air quality can be affected by these factors. These factors may cover most of economic, social, political, cultural areas, so that we will be able to look at air pollution issues from a bigger picture instead of air itself.
  
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.
+
'''''
  
 
||
 
||
*[[Group10_Overview|Proposal]]
+
*[[Group23_Proposal|Proposal]]
*[[Group_10_Poster|Poster]]
+
*[[Group23_Poster|Poster]]
*[[Group_10_Application|Application]]
+
*[[Group23_Application|Application]]
*[[Group_10_Report|Report]]
+
*[[Group23_Report|Report]]
 
||
 
||
* Aishwarya Mohan
+
* LIAO YUNXIA
* Deng Chunling
+
* HU YUNXIA
* Ma Xiaoliu
 
 
|-
 
|-
 +
 +
||
 +
<div style="text-align:center;">
 +
[[File:Cricviz.png|250px]]
 +
</div>
 +
 +
||
 +
'''CricViz: Indian Premier League'''<br>
 +
'''''
 +
Cricket, the second most popular sport in the world, is a bat and ball game played between two teams, 11 players each, on a field which has a rectangular 22-yard-long pitch in the center. The game is played by 120 million players worldwide and the purpose of the game is to score more runs than your opposing team.
 +
 +
The Indian Premier League (IPL), is a professional Twenty20 Cricket League in India contested during April and May of every year by teams representing Indian cities and some states. The league was founded by the Board of Control for Cricket in India (BCCI) in 2008.
 +
 +
This project is about exploring the statistics of historical IPL data of 8 seasons (2008-16) to understand patterns in individual player performance, team strengths & weaknesses, find the Most Valuable Players (MVPs), and thus suggest the best IPL team for each season, amongst others.
 +
'''''
 +
 +
||
 +
*[[ISSS608_2017-18_T1_Group24_Proposal|Proposal]]
 +
*[[ISSS608_2017-18_T1_Group24_Poster|Poster]]
 +
*[[ISSS608_2017-18_T1_Group24_Application|Application]]
 +
*[[ISSS608_2017-18_T1_Group24_Report|Report]]
 +
||
 +
* Saurav Jhajharia
 +
* Gaurav Miglani
  
 
|-
 
|-
 +
 
||
 
||
[[Group_11_Overview|Group 11: CrimeModeler: A Visually-Driven Geospatial Modelling Tool for Crime Applications]]<br><br>[[File:police.jpeg|220px|center]]
+
<div style="text-align:center;">
 +
[[Group25_Overview|Group25]]
 +
[[Image:Group25_Logo.png|250px|center]]
 +
</div>
 
||
 
||
'''CrimeModeler: A Visually-Driven Geospatial Modelling Tool for Crime Applications'''
+
'''Singapore Bus Services - Perfection is not a destination; it is a continuous journey that never ends'''<br>
  
Based on UN’s Survey of Crime Trends published in 2006, England and Wales have one of the highest crime rates among OECD countries. We have developed CrimeModeler, a geospatially modelling tool to investigate the spatial variation of crime across different districts in England and Wales, and the relationship between crime and socio-economic characteristics for each district. As it is common for neighbouring regions to have correlation in their crime rate, we compare the use of geographically weighted regression (GWR) and conventional (or global) multiple regression model to see whether a better result can be obtained from GWR. We will also investigate whether there are certain variables that have an impact on crime rate in one area but not in another. Local governments may use this information to come up with better policies to tackle crime.
+
'''''
 +
Buses form a significant part of public transport in Singapore, having extensive network of routes covering most places in Singapore, with over 3.9 million rides taken per day on average as of 2016, and is the most economical way to get around. However, despite being crowned as one of the most efficient bus transportation services in the world, there is always room for improvements, especially passenger satisfaction.
  
 +
Our objective is to suggest ways to increase the efficiency and optimization of the current Singapore bus route by visualizing some of the problems the current Singapore bus services have. Our main target is buses that have unusually long travelling time. If we successfully suggest ways to split the buses, not only we will be able to reduce travelling time (thus reducing cost related problem), but we will also able to reduce overcrowding problem and in turn increase passenger satisfaction.
 +
 +
'''''
  
 
||
 
||
*[[Group11 Proposal|Proposal]]
+
*[[Group25_Proposal|Proposal]]
*[[Group11 Poster|Poster]]
+
*[[Group25_Poster|Poster]]
*[http://crime.raymondfoo.host/ Application]
+
*[[Group25_Application|Application]]
*[[Group11 Report|Report]]
+
*[[Group25_Analysis|Report]]
 
||
 
||
* Raymond FOO Celong
+
* Anthony Theodore
* Anthony GOH Jun Jie
+
* Aparajita Shukla
* Karan Jyoti KHANNA
+
* Vishali Reddy Nalla
 
|-
 
|-
  
 
||
 
||
 
<div style="text-align:center;">
 
<div style="text-align:center;">
[[Group12_Proposal|Group 12:Cross Shareholding]]<br><br>[[File:Group12Title.JPG|209px|center]]
+
[[Group26_Overview|Group26]]
 +
[[File:Picture.jpg|320px|center|link=https://wiki.smu.edu.sg/1718t3isss608/Group26_Proposal]]
 +
</div>
 
||
 
||
'''Cross Shareholding'''
+
'''ALWAYS A WAY OUT -- Alternative Trade Markets Analysis for China'''<br>
  
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.
+
'''''
 +
The 2018 China-United States trade war began after U.S. President Donald Trump announced, on March 22, 2018, an intention to impose tariffs of US$50 billion on Chinese goods under Section 301 of the Trade Act of 1974, citing a history of "unfair trade practices" and theft of intellectual property. In retaliation, the Chinese government imposed tariffs of their own on over 128 U.S. products, including most notably soybeans, a major U.S. export to China.
  
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 terms of the trade war itself, the world’s two largest economies threating to impose tariffs will have a very direct and negative impact on global economy. Which markets can be potential destination for the exportation giant China? Who can help absorb the surplus supply? Deploying visualisation tools can help find the answer.
  
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.
+
'''''
  
 
||
 
||
*[[Group12 Proposal|Proposal]]
+
*[[Group26_Proposal|Proposal]]
*[[Group12 Poster|Poster]]
+
*[[Group26_Poster|Poster]]
*[https://koreastockcrossholding.shinyapps.io/ksch1203/ Application]
+
*[[Group26_Application|Application]]
*[[Group12 Report|Report]]
+
*[[Group26_Report|Report]]
 
||
 
||
* KYONG HWAN KIM
+
* LU Yanzhang
* GONGQIANG
+
* LUO Haoran
* HE ZIWEN
+
* SUN Shuangtian
 
|-
 
|-
  
 +
||
 +
<div style="text-align:center;">
 +
[[File:New-York-City-Brooklyn-Bridge-Panorama-Juergen-Roth-2.jpg|400px|centre|link=Group27_Overview]]
 +
[[Group27_Overview|Group27]]
 +
</div>
 +
||
 +
'''Airbnb's impact on affordable housing in New York'''<br>
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Community groups and housing advocates in cities across the world have begun to sound the alarm about the impact Airbnb is having on affordable housing in their communities, citing concerns about housing supply lost. We chose New York, a typical Airbnb city, as an entry point to understand Airbnb’s impact on housing. We aim at presents a comprehensive visual analysis of 3 years from 2015 to 2017 of Airbnb activity in New York City. It relies on the most comprehensive third-party dataset of Airbnb activity available, and methodologies of visualize and analysis geographical data.
 +
 +
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Our report is motivated by the concerns increasingly raised by local communities and housing advocates that short-term rentals are clearly affect traditional residential rental housing and hotel accommodation. But reliable, up-to-date evidence has been hard to come by. Accordingly, we want to explore the Airbnb activity in New York City, discovering different neighborhood’s distinct characteristics by Geospatial pattern analysis across 3 years. Meanwhile, we go further to to investigate the impact on housing market, which leads to lower affordability housing, housing supply lost, and then cite the emphasis on illegal rental and huge potential benefit on Airbnb-ed, which is the underneath motivation of shifting listing from rental market to Airbnb Website.
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*[[Group27_Overview|Proposal]]
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*[[Group27_Poster|Poster]]
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*[[Group27_Application|Application]]
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*[[Group27_Report|Report]]
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* Li Zidan
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* Li Yaru
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* Meng Xiangyi
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Latest revision as of 16:50, 17 August 2018

Vaa1.jpg ISSS608 Visual Analytics and Applications

About

Weekly Session

Assignments

Visual Analytics Project

Course Resources

 


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

Project title: Provide eyes catching title. However, it should reflect the content or/and the focus of your project

Abstract

The abstract should not be more than 350 words.

  • Member 1
  • Member 2
  • Member 3

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Cyber-security: you are in more danger than you can possibly imagine

Cyber-attacks are becoming increasingly sophisticated. Coupled with the growing amount of data being generated by individuals, corporations and governments, well-orchestrated attacks could potentially cause major disruptions to any country, such as gaining access to national defense systems. According to David Koh, CEO of Singapore’s Cyber Security Agency, Singaporeans are largely aware of cybersecurity threats but do not take the necessary precautions, which may be due to complacency stemming from Singapore's reputation as a safe country1. Hence, public education is still required to urge individuals into taking preventive measures. This project will contribute to that end by providing interactive and interesting visulisations of cyber-attacks that can engage members of the public.

1https://govinsider.asia/innovation/cyber-war-csa-singapore-david-koh/


  • Lim Yee Cheng
  • See Kwan Yen
  • Zheng Weijie Jay
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World Energy Production & Consumption:
A Visual Study

For 66 years, the BP Statistical Review of World Energy has provided high-quality objective and globally consistent data on world energy markets. The review is one of the most widely respected and authoritative publications in the field of energy economics, used for reference by the media, academia, world governments and energy companies. A new edition is published every June.

Join us as we explore the rich data-set provided by BP & study the dynamics of regional energy production and consumption of the different countries of the world to identify the dominant as well as weaker player in the world energy market.

  • Aakanksha Kumari
  • Amrutha Rajeshwari Yejerla
  • Priyanka Sharma

alt text = "Group 03"

Perceiving Evil: The Study of the Corruption Perception Index


First launched in 1995, the Corruption Perceptions Index (CPI) has been widely credited with putting the issue of corruption on the forefront of the international policy agenda. It score countries on how corrupt their public sectors are seen to be. By marrying the data set from Transparency International on their CPI records through the years versus the World Bank data set, which contains World Development Indicators (WDI) of the same countries, we will try to find out if there is indeed any correlations between the perceived corruption level of a country, and its actual conditions.

Is it true that a corrupted country is naturally poor? Are GDP growth linked with corruption? Does the gender composition of the country affects corruption? We will try to find out here.

  • Jan Patrick Mabilangan Gosioco
  • Winston Lim Wee Kiong
  • Yeo Kaijun
ISSS608 Group4 Icon.png

Water For Life: Effect Of Rainfall On India's Crop Productivity

Climate change has a serious impact on the availability of various resources on the earth especially water, which sustains life on this planet. One occupation that has experienced a direct impact due to these increasing climate fluctuations is Agriculture. Especially in a country like India where water, the most critical agricultural input is scarce. Nearly 55% of the total cultivated areas in India do not have irrigation facilities. And hence Indian farmers are highly dependent on rainfall as rainfall is the fundamental driver of water availability for agriculture. Changes in precipitation affect the quality and quantity of the agriculture produce in direct proportions of the rainfall received.

In this study, we intend to analyse India’s rainfall pattern for past few years using various exploratory techniques, primarily focusing on apt visualizations to reveal the undiscovered truth. Over 80% of the annual rainfall is received in the four rainy months of June to September. There is great regional and temporal variation in the distribution of rainfall and although the monsoons affect most parts of India, the amount of rainfall varies from heavy to scanty on different parts. The primary motive of our analysis is to scrutinize the effect of irregularities in the rainfall pattern on agricultural productivity in India. Through our analysis, we would like to derive meaningful insights that foster our understanding about the most affected regions and crops because of the variability in climactic change so that actionable recommendations could be sought from the final developed application.

  • Akanksha Shrirang Yadav
  • Jyoti Bukkapatil
  • Pooja Manohar Sawant

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Exploring Inequality’s Geographic Dimension Across Neighbourhoods in Singapore: Its Driving Forces & Touch Points

Amidst the recent debate over growing social inequality in Singapore such as the distinct clustering of elite schools and varying access to resources, the dangers of hardening social mobility pose as a concern for a culturally diverse nation that has upheld its values of social cohesion and racial harmony. In bridging social divide, Singapore has put in place various community programmes to create shared experiences and promote inter-communities mixing.

Using geospatial techniques in R, the dashboard serves to explore the geographic dimension of social inequality, by mapping the extent of social segregation and accessibility to important spaces across neighbourhoods. This is done in three approaches. First, we analyse whether there exists social segregation across subzones using the Entropy-Based Diversity Index, based on three dimensions of inequality - race, age and housing type. Second, using spatial point pattern analysis at the HDB postal code level, we visualise whether there exist housing type clusters that could point towards social inequality and whether certain towns are overpopulated with a specific housing type. Third, using the Hansen Accessibility Model, we map out available touch points that could facilitate social mixing, particularly the ease of access to primary schools. We also see whether there is any variation in accessibility between the elite and mainstream primary schools for different housing types. This is because an important aspect of social inequality is having reasonably fair access to resources. Lastly, we move into solutioning and explore whether there exist sufficient common spaces that allow for social mixing, such as parks, and identify areas that are underserved for urban planners to focus their attention on for future space planning.

  • CHAN EN YING GRACE
  • LIU YUQING
  • LIU YUANJING

Buy More! – Maximizing Revenues

Taking advantage of data is key to ensuring the survival of an e-commerce retail business. Through the visualization of the spending habits of customers and the visualization of the results from various machine learning algorithms, insights can be gathered as to which customers the retailer should target and what type of products should be kept in-stock to maximize sales.

An e-commerce company in the United Kingdom has provided their transaction data from 1 December 2010 to 9 December 2011. This company mainly has wholesalers as its customers. Based on the data provided, the company’s client portfolio is mainly based in the United Kingdom.

On the market, there are various customer intelligence platforms available: “DataSift”, “SAS Customer Intelligence”, “Accenture Insights Platform”, etc. However, none of them are offer an integrated bespoke solution for our data on hand. Our motivation is to build an entirely bespoke application that would allow the company to fully analyse their data right at the onset and thus maximize the revenue of the company.

  • ZHANG Yingdi
  • FU Chuanjie
  • WANG Runyu

Singapore Property Market Watch - Your new tool to visualize SG Property Trend

"Have your heard that Singapore IRAS just increased Additional Stamp Duty rate (ABSD)?! And US Federal Reserve will increase the interest-rate again?! How does Singapore Property market going to change now, we wanna see market trend leh, but how?"

There is a deficiency of Market Watch tool for analysing the real estate market data as well as the trends properly. As it is very important to show the trendline cross different years and time, however, these data are still in table formats and the visualizations are quite basic, most of trends are illustrated statically, static graphs are not explanatory enough to show a full picture of changes, which sets barriers for readers from getting any useful insights and findings.

To better understand how the Real Estate market price moves cross different type of sales, property types and planning areas in the last 20+ years. Our team will provide an unbiased visualization tool for readers to understand and compare the Property Market pattern changing overtime.


  • Fu Yi
  • Orkhan Hasanli
  • Tan Yong Ying, Joanne

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Group 8:
Understanding gender equality from a visual perspective

With the improvement of quality of life across the world, the argument for various freedoms and rights surface and turn to hotly debated topics especially in highly developed countries. One such agenda is the push for the empowerment of women, amongst the fight against other forms of discrimination.

Given the growing importance on this area, our project seeks to encapsulate existing data and present it visually in a simple, understandable manner, to help further efforts in driving the agenda. Using graphical techniques complemented with some level of statistical modelling in R, our dashboard will provide a view on changing patterns in key indicators relating to gender equality and women empowerment with time, as well as attempt to highlight important variables which aid the growth of such indicators.

  • Low Zhi Wei
  • Shi Chen
  • Yi Xiaoqin

Contagious diseases analysis in US
Healthcare and diseases are the major concerns over past centuries. The germ theory of disease in the 19th century led to cures for many infectious diseases, at the same time, public health measures developed as the rapid growth of cities required systematic sanitary measures. Although Researches of contagious diseases are abundant, they are still mystery for the public due to their exclusion to the specialists.


Recently, contagious diseases such as malaria, influenza A(H5N1) virus (avian flu) and severe acute respiratory syndrome(SARS) reach high epidemic proportions in some countries, especially for developing countries. Studying the patterns of contagious diseases still is significant for recent healthcare industry, moreover, it is not only the specialists’ mission, with the help of technology, even the public have the privileges to explore such patterns. Thus, we intend to apply visual analytics technique and graph theory to visualise historical records of seven contagious diseases: Smallpox, Rubella, Hepatitis, Measles, Polio, Mumps, Pertussis from US during year 1916 to 2010 and to visualise the relationships among these seven diseases and their symptoms. This project aims at 1) build a two-mode network and apply graph theory to visualize how contagious diseases are related to their symptoms; 2) visualise the historical records for finding patterns over these typical contagious diseases so that can apply the findings to other diseases.

  • Chen Runpu
  • Chen Yanchong
  • Yang Zhengyan

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Hello Shiny! - Voice integrated Visual analytics

Global migration flows: With the world shrinking by the day with technology and humans being more than ever ready to scale distances in quests to follow a career path or to escape political persecution and war or in search of better quality of life or to be closer to family or friends, Migration and the resulting ethnic and racial diversity are amongst the most emotive subjects in contemporary societies. In recent times, the political salience of migration has strongly increased due to uproar of natives and other factors. For origin societies, the departure of people raises concern about the 'brain drain' on the one hand. For receiving societies, the settlement of migrant groups and the formation of ethnic minorities can fundamentally change the social, cultural, economic dimensions and cause lack of resources for the natives.

Using R’s geospatial and quadrant analysis techniques, we aimed to delve into the migrant numbers data over the years from country to country conjoined with the remittances according to the world bank by them to the origin locations. Migration and remittance numbers will be analysed grouping the locations on continent, region and socio-economic status scales to identify relations between the factors separating the dominating and the dominated societies. A balance model was applied to analyze the migration flows between countries of the same development level.

The visualizations are linked between each other and wrapped on to an interactive application which can be controlled by user voice inputs, we will be using a Javascript library interfaced to R shiny to control the application’s select, filter and switch inputs.

  • Kaushik JAGANATHAN
  • Priyadarsan SHANKAR
  • SONG Xuejing
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New York City Crime Watch

Crime is an act punishable by law that has been timeless is prevalent in every society. Crime activities are recorded for crime analysis which involves systematic analysis for identifying and analyzing patterns and trends in crime and disorder.

For our crime analysis, we have used the New York Police Department (NYPD) crime data for the which spans crimes records across the 5 boroughs of NYC. We aim to provide a visual tool to observe the crime patterns with respect to time and location. On doing this, the rate of crime can be analyzed and hence forecasted for law enforcement agencies can estimate the right number of resources to deploy.


  • Diya Naresh Rao
  • Nevil Bruno
  • Vishal Badrinarayanan

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Group 12
Have the Nations really progressed? - Story from World Bank statistics


For almost a hundred years, two measurements have been used to get a sense of how well a country is doing. One is GDP, the other is its unemployment rate. But when it comes to figuring out how well a country is serving its citizens; these two might not be the only metrics to gauge a nations collective progress. On estimates of social progress, poorer countries often outdo their wealthier counterparts. Social progress is not completely explained by economic variables like GDP data. It can show surprising relationships that help shape policy. One of the interesting ways these kinds of indexes are used is to see how countries have improved or declined – or just stayed the same. It can determine which countries get help with funding. And it may even be able to help predict the future.

Through our visualizations, we seek to utilize existing data to derive meaningful insights over how various socioeconomic factors have had an impact on development of different nations. Using graphical techniques in R, our dashboard will feature analysis on key indicators relating to financial, educational, gender, health, industry & demographic as well as attempt to highlight important variables which aid their growth.

  • Sudhir Panda
  • Lokesh Vairamuthu
  • Sameer Panda

G13 Logo.jpg

Man - KIND?

The Organization for Economic Co-operation and Development is an intergovernmental economic organization with 37 member countries, founded in 1961 to stimulate economic progress and world trade. Most OECD members are high-income economies with a very high Human Development Index (HDI) and are regarded as developed countries. As of 2017, the OECD member states collectively comprised 62.2% of global nominal GDP (US$49.6 trillion) and 42.8% of global GDP ($54.2 trillion) at purchasing power parity.

But has this economic progress come at a cost?
Is there a relation between the growth factors versus the environmental damage imposed by these nations?
Do the Emission, Green Energy, and Economic Growth Indicators have a story to tell?
What factors, if any, binds certain clusters of similar performing nations?

Join us on our data visualisation expedition as we attempt to explore some facts based on a 10 years OECD data.


  • Harisingh Khedar
  • Kiriti Yelamanchali
  • Suhas Awasthi

Towards Greater Transparency for the Global Arms Trade

The global arms trade has been a major concern as the international transfer of arms between states could lead to wars, crimes against humanity and contribute to serious violations of international human rights. The Stockholm International Peace Research Institute (SIPRI) collects data on arms transfers between regions and states aimed at increasing the fundamental understanding of the impact of arms transfers and to support policymaking. Based on the latest publication by SIPRI, a rising trend is observed in the volume of international transfers of major weapons, with the highest volume of arm transfers recorded between 2013 to 2017, since 1990.

Our project aims to use interactive visualisation to identify the trends and patterns in the international arms transfers and to explore the arms trade dependencies between countries and regions.


  • Tong Wen Liang Samuel
  • Miko Tan Mei Jia
  • Kalai Selvi

Bird, Where Art Thou?

Animal migration has long received much attention as a research topic in biology. Information about animal movement serves to allow us to understand animal behavior and their interactions with each other and the environment. In addition, it allows us to address environmental challenges such as climate and land use change.

Understanding animal migration helps conservationists to conserve these animals through the protection of their habitats and their resources.

An interactive visual analytics approach would provide valuable insights to the scientific community on the migration of these animals.


  • Chen, Pin-an
  • He Mengqi
  • Ong Wah Jie


VA-logo greens.png


Urban Pulse —— Visualization on Beijing's Traffic
In Beijing, traffic problem is always a shared concern among citizens. As China urbanizes, more and more people flood into first-tier cities, which has caused severe traffic congestions. Beijing is obviously on the top congestion city list. With taxi trajectory data collected by Microsoft from over 10,000 taxis in Beijing, this case aims to uncover traffic patterns through static and dynamic visualization and combine these findings to city construction to discover possible reasons behind these patterns. More over, suggestions will be given for three parties: urban road planning optimization for government, efficient taxi resources arrangement for taxi companies, and travel advice for citizens in Beijing.

  • ALEJANDRO LLORENS MORENO
  • JIANG YILIN
  • LI HONGXIN

GeBiz: Who supplies to the needs of Singapore?

Government Procurement is the procurement of goods and services on behalf of a public authority. As per policy, the procurements need to be done through an issue of public Tenders to prevent corruption, wastage, and local protectionism. GeBiz is the Singapore government's one stop portal for the above purpose. The data of past procurements are made available for the public in the Data.gov.sg portal. It is difficult to identify bias in such data available that have multiple transactions. Since a transaction involves various levels of the government, the bias may not be obvious while looking at the issuing authority and the supplier alone.

We propose an approach which combines network analysis, association analysis, and visual analytics to make this process easier. Traditionally, Association analysis has been used to identify relations between products purchased together. It is also applicable to any data that follows the format of multiple entities and a common transaction that links them together. In our case, the entities involved are the issuing agency and the supplier. The current visualizations treat all entities involved to be of the same category, thus making the visualization less intuitive. We want to come up with a visualization that can overcome this limitation.

  • Joel Choo Peng Yeow
  • Manu George Mathew
  • Minami Yusuke
Crime India Logo.gif

A sanctuary for women – Is there one?

Crime against women in India is very old social issue which is prevalent in almost all societies. It is increasing day by day and deeply rooted in the Indian society even after increasing education level of people. Inefficient legal system, weak rules of laws and patriarchal society in the second most populous country are few factors attributing and triggering increase in crime against women. The recent public outcry following a brutal gang rape of a young woman in India's national capital was a watershed moment in the world's largest democracy. The hype in the media across the world compels us to believe that crimes against women in India is on a dramatic rise.In our analysis, we take a step forward in this direction to discover the hidden truth in the Women Crime data using visualization techniques to better understand crime occurrences against women in India.

  • Alagu Alagappan
  • Rupini Sinnan Chettiar Pandian
  • Vigneshwar Vadivel
Group19 Logo.jpg

Male or Female, that is a question!!

Based on “The Global Gender Gap Report 2017”, China remains the world’s lowest ranked country with regard to the gender gap in its sex ratio at birth. Tracing back to previous census data and demographic statistics, sex ratio at birth in China has been on the high side since the early 1980s and rising continuously. In this project, We try to find out the socio-economic and cultural factors that leading to the increase of the sex ration at birth, which may be meaningful to curb the increase of birth sex ratio and restore it to normal level.

  • Bi, He
  • Chen, NanNan
  • Teng, Fei

The air quality in China

Like other countries, China has to date followed a pattern of grow first, clean up later. Many developed cities have serious environment problems. Particularly, in 2015, Beijing had experienced heavy smog for 6 months and severe polluted days for more than 1 month. Everyone was talking about air quality and health. In recent years, government has put the green development in the first place, so dose our air quality become better?

To understand the improvement of air quality of developed cities and the impact of air quality on the health of residents, we choose four first-tier cities (Beijing, Shanghai, Shenzhen and Guangzhou) and 15 new first-tier cities (Chengdu, Hangzhou, Wuhan, Nanjing, Chongqing, Tianjin, Suzhou, Xian, Changsha, Shenyang, Qingdao, Zhengzhou, Dalian, Dongguan and Ningbo) to analyze.

  • Chen Fan
  • Huang Yiyun
  • Xie Zhimao

MOVE TO WHAT MOVES YOU!

With inflation in prices of land and an increase in human population, the Real Estate Market in Singapore has seen high volatility over the years. We observe that the market has significantly higher demand than supply, thereby creating a dilemma for people about the kind of property they should invest in. Our project is based on real estate sales data for 2017-2018 and provides transaction details, data on Flat Model, Flat Type, Lease and other relevant details. Through the scope of this project, we intend to provide a detailed understanding of the real estate market so that the users of the application can make a more informed decision. We believe that real estate agents and brokers, economists, investors and other enthusiasts can use the application to understand market trends and make investment decisions.

  • Vaishnavi Agarwal
  • Param Gadhaiya

Small loan, Big difference

Kiva is an international non-profit, founded in 2005 and based in San Francisco, with a mission to connect people through lending to alleviate poverty. Kiva celebrates and supports people looking to create a better future for themselves, their families and their communities. What we try to do is helping the website extend to more countries and helping more people solve the survival problems.

  • YU,ZHECHENG
  • GAO,JIAOYANG
  • MU,FUYAO

Air Pollution.jpg

MAKE THE WORLD A BETTER PLACE TO “BREATHE”


Air pollution, as one of most fatal and yet invisible pollution in the world, is also one type of pollution we can’t escape from. It’s in the air we breath in and out and it’s causing threats to all living creatures on this planet. However, as research done by World Health Organization (WHO) shows, till 2016, the air pollution level has again, risen by 8%. Every nature sign urges for immediate actions upon improvements IN air quality, but HOW?

Our project aims to create a collaborative interface to track for everything that is happening in the world and to which extent air quality can be affected by these factors. These factors may cover most of economic, social, political, cultural areas, so that we will be able to look at air pollution issues from a bigger picture instead of air itself.


  • LIAO YUNXIA
  • HU YUNXIA

Cricviz.png

CricViz: Indian Premier League

Cricket, the second most popular sport in the world, is a bat and ball game played between two teams, 11 players each, on a field which has a rectangular 22-yard-long pitch in the center. The game is played by 120 million players worldwide and the purpose of the game is to score more runs than your opposing team.

The Indian Premier League (IPL), is a professional Twenty20 Cricket League in India contested during April and May of every year by teams representing Indian cities and some states. The league was founded by the Board of Control for Cricket in India (BCCI) in 2008.

This project is about exploring the statistics of historical IPL data of 8 seasons (2008-16) to understand patterns in individual player performance, team strengths & weaknesses, find the Most Valuable Players (MVPs), and thus suggest the best IPL team for each season, amongst others.


  • Saurav Jhajharia
  • Gaurav Miglani

Singapore Bus Services - Perfection is not a destination; it is a continuous journey that never ends


Buses form a significant part of public transport in Singapore, having extensive network of routes covering most places in Singapore, with over 3.9 million rides taken per day on average as of 2016, and is the most economical way to get around. However, despite being crowned as one of the most efficient bus transportation services in the world, there is always room for improvements, especially passenger satisfaction.

Our objective is to suggest ways to increase the efficiency and optimization of the current Singapore bus route by visualizing some of the problems the current Singapore bus services have. Our main target is buses that have unusually long travelling time. If we successfully suggest ways to split the buses, not only we will be able to reduce travelling time (thus reducing cost related problem), but we will also able to reduce overcrowding problem and in turn increase passenger satisfaction.


  • Anthony Theodore
  • Aparajita Shukla
  • Vishali Reddy Nalla

ALWAYS A WAY OUT -- Alternative Trade Markets Analysis for China


The 2018 China-United States trade war began after U.S. President Donald Trump announced, on March 22, 2018, an intention to impose tariffs of US$50 billion on Chinese goods under Section 301 of the Trade Act of 1974, citing a history of "unfair trade practices" and theft of intellectual property. In retaliation, the Chinese government imposed tariffs of their own on over 128 U.S. products, including most notably soybeans, a major U.S. export to China.

In terms of the trade war itself, the world’s two largest economies threating to impose tariffs will have a very direct and negative impact on global economy. Which markets can be potential destination for the exportation giant China? Who can help absorb the surplus supply? Deploying visualisation tools can help find the answer.


  • LU Yanzhang
  • LUO Haoran
  • SUN Shuangtian

Airbnb's impact on affordable housing in New York

Community groups and housing advocates in cities across the world have begun to sound the alarm about the impact Airbnb is having on affordable housing in their communities, citing concerns about housing supply lost. We chose New York, a typical Airbnb city, as an entry point to understand Airbnb’s impact on housing. We aim at presents a comprehensive visual analysis of 3 years from 2015 to 2017 of Airbnb activity in New York City. It relies on the most comprehensive third-party dataset of Airbnb activity available, and methodologies of visualize and analysis geographical data.


Our report is motivated by the concerns increasingly raised by local communities and housing advocates that short-term rentals are clearly affect traditional residential rental housing and hotel accommodation. But reliable, up-to-date evidence has been hard to come by. Accordingly, we want to explore the Airbnb activity in New York City, discovering different neighborhood’s distinct characteristics by Geospatial pattern analysis across 3 years. Meanwhile, we go further to to investigate the impact on housing market, which leads to lower affordability housing, housing supply lost, and then cite the emphasis on illegal rental and huge potential benefit on Airbnb-ed, which is the underneath motivation of shifting listing from rental market to Airbnb Website.

  • Li Zidan
  • Li Yaru
  • Meng Xiangyi