Project Groups
ISSS608 Visual Analytics and Applications
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Project Groups
Please change Your Team name to your project topic and change student name to your own name
| Project Team | Project Title/Description | Project Artifacts | Project Member |
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Transport Data from EZlink Singapore is a highly urbanised city state with a good network of public transport. It is important to understand how the population flows within the city state through the public transport system. The public transport planners will need to understand the characteristics of the population commuting on the public transport system, especially the public bus system. The public bus system has a greater reach to majority of the population and is more dynamic in nature as compared to the train system. By understanding the characteristics of the commuters, it will allow the planners to twist the public bus system in order to make it more efficiency and support the initiative of a car-lite society.
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Analysing Rise in Temperatures and Its Causes Globally Through Interactive Visualizations Climate change and global warming are material and contemporary issues that are gaining traction from countries all over the world. Global citizens of all ages and economic backgrounds are faced with unwanted effects of climate change today. As the buzz around global warming continues to increase, this contemporary issue has incited many relevant visualisations. Through this project, we analyse the key contributors to climate change namely: Fossil fuel consumption, adoption/rejection of renewable energy, electricity consumption, deforestation rate, and greenhouse gas emissions. The residual impact of these factors to facilitate the rise of global temperature has been captured for 86 countries around the world. While most contemporary visualisations focus on individual environmental hazards such as increased rates of carbon emissions or the rapid rise in temperature, our analysis attempts to connect the dots to better understand the cause-and-effect nature of global warming. Through our visualisations, we depict the causal effect between the factors which contribute to greenhouse gas emissions and the resulting impact on increase in temperature from the year 1990 to 2012. Furthermore, we attempt to forecast the aforementioned causal effects and the net rise in temperature for ten subsequent years to better understand the variation in each factor over time. |
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[[Smartie Mall|Group 3 - Team S-MALL]| |
VAST Challenge 2016 – Return to Kronos (Mini challenge 2) This challenge involves analysis of a collection of static data about two weeks of GAStech operations data, including building sensor readings and prox-card movement throughout the building. Deliverables include interesting patterns, anomalies/unusual events that are most likely to represent a danger or a serious issue for building operations, and relationships between the proximity card data and building data elements.
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A Peek into University Ranking - A Visualization University ranking is always one consideration for to-be applicants. There is a certain prestige in having a better ranking, and universities generally work towards having better standing. According to Kaggle, "Ranking universities is a difficult, political, and controversial practice." Through this visual analytics project, we look to analyse the world distribution of these universities, its attributes, rankings over time, and seek to draw insights from them. |
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Geo-spatial analysis of vehicle movement data to uncover patterns and detect anomalies Geo-spatial analysis is a subject of growing interest owing to numerous reasons - but a clear driver is data availability and data accessibility. The rise of the sensors and IOT era has made data capture by independent organizations and bodies plausible and this improves accessibility to movement data which was earlier limited to usage by government bodies and leading researchers. Our study utilizes data from a Natural Preserve to explore vehicle movement patterns. The scope includes the analysis and visual representation of frequency related findings such as ‘peak and non-peak periods’ and route related findings such as ‘path navigation through the preserve’ with the aid of interactive dashboards. The primary framework used for analysis and visualization is rShiny. There are several packages in R that enable us to create a seamless interactive interface for connecting and exploring the data. We have incorporated calendar heat maps to understand the peak and non-peak cycles across months, day of the weeks and hour of the day. This has enabled us to plot all the movement data over time on a single view. The patterns and trends identified can be used to drill down for further exploration. The route taken by the vehicles was explored using Sunburst diagrams. This has been used to view a summary of the paths taken and understand the more popular paths. Common destinations and starting points can be easily identified and compared. The interactive dashboards have been developed to accommodate the analysis of other sources of movement related data to retain reusability of dashboards and extend its usage for other purposes where deemed suitable. Future works can include incorporating speed related elements in analysis. |
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Even though Zika virus has been identified as early as in 1940s, it wasn't widely reported till it outbroke rapidly in south America in 2015. In Singapore, the first case was found in August 2016. Within 2 months, there are more than 400 cases identified locally. In this project, we will exam spread pattern of the Zika virus, are there any relationship between the weather or geolocation and the spread of this virus. |
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Are You Happy? Abstract |
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Visualising Terrorism In recent years, terrorism attacks in the western world are the centre of focus and receive extensive reporting. However, terrorist attacks in the Middle East, South America, Africa and South Asia often receive much less attention or totally neglected. This creates a perspective that is far from the truth. We aim to present a holistic picture of the global terrorist attacks: across time, countries, targets and methods, to help the viewers have a better understanding of terrorist attacks in various countries during different periods of time. As such, we have built an interactive dashboard visualisation that showcases the changes in terrorist attacks from 1985 to 2016. |
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Visualising Twitter: Hashtags and User Mentions Network Twitter is described as the SMS of the internet. When key events occur, knowing the buzz from an information network such as Twitter tells you the present. Our aim is to visually analyze the association of #tags, representing a key idea, with @mentions. |
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European Football Visualization One of the most popular sports worldwide is football. Football can be considered as the most favourite sport in the world, especially in Europe. The motivation of this project is to discover interesting findings about the top 4 leagues in Europe. (England, Spain, Italy, Germany) |
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IMDb The project aims to enable the user to explore various aspects of IMDb data set through interactive visualization tools and techniques. |
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Cancer in U.S.
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Video Game Analytics Vgchartz.com, is a video game sales tracking website that provides weekly sales figures of console software and hardware by region. The site was launched in June 2005 and is run by a small team of ten. Presently, users find the visualizations time consuming, difficult to comprehend and navigate.
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A View at HDB Car Parking System The HDB car parking system in Singapore is a very mature one. This project aims to visualize this car parking system. The various types of car parking are understood and visualized. These car parking systems are broken down area-wise and block-wise and visualized using various tools and visualizations such as hierarchical tree and sunburst diagrams. |
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A View at HDB Car Parking System The HDB car parking system in Singapore is a very mature one. This project aims to visualize this car parking system. The various types of car parking are understood and visualized. These car parking systems are broken down area-wise and block-wise and visualized using various tools and visualizations such as hierarchical tree and sunburst diagrams. |
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Characterising Pandemic Spread Using R A pandemic is an epidemic or outbreak of infectious disease that spreads rapidly not only to many people, but across countries. The unprecedented mobility of people and food over the last 30 years has seen a steady increase in the frequency and diversity of disease outbreaks. No country is immune to this growing global threat. Scientists are predicting that it is not a matter of if, but when the next pandemic will happen. Singapore, as a small city state, with the highest population density in the world and one of the highest air passenger traffic, is particularly vulnerable. There are reasons to remain optimistic, as Singapore’s SMART Nation initiatives and modern healthcare systems’ electronic records have open up new possibilities in the fight against potential infectious disease outbreaks in the country. Data will be increasingly ubiquitous as the world, including Singapore, continues to make significant advancement in the digitalisation age. Insights from the data have the potential to offer a critical line of preparedness needed through early identification, rapid effective response, and containment of disease outbreaks. Using R programming to analyse a synthetic dataset (i.e. computer- and human-generated data) relating to a major disease outbreak that spanned several cities across the world in 2009, we have developed a visualisation tool and deployed it as an interactive dashboard prototype via R Shiny. This visualisation tool can potentially be used by health officials to analyse the hospitalisation data and characterise the spread of the pandemic across countries should an actual disease outbreak happen. We have demonstrated the capabilities of this visualisation tool through the use of calendar heatmap, trellis plot and other new visualisation graphing methods. The efficacy of each of these visual analytics techniques will be discussed in detail. We will also suggest possibilities for future works by combining hospital records with other data sources. |
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A View at HDB Car Parking System The HDB car parking system in Singapore is a very mature one. This project aims to visualize this car parking system. The various types of car parking are understood and visualized. These car parking systems are broken down area-wise and block-wise and visualized using various tools and visualizations such as hierarchical tree and sunburst diagrams. |
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Project Groups
Please change Your Team name to your project topic and change student name to your own name
| Team | Members | |||||||||||||||||
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| Investigation of vehicle traffic corridors using visual analytics | Kishan Bharadwaj Shridhar | Ong Guan Jie Jason | Zhang Yanrong | |||||||||||||||
| Global Warming: A Tale of Rising Temperatures | Angad Srivastava | Akangsha Bandalkul | Dipti Kalyandurgmath | |||||||||||||||
| S-MALL | Chen Yun-Chen | Chiam Zhan Peng | Zheng Bijun | Ghost Lin | ||||||||||||||
| Group 4 | Akanksha Mittal | Sivagamy Balamourougane | Sanghavy Balamourougane | |||||||||||||||
| Group 5 | Vincent Mack Zhi Wei | Chen Xiaoqing | David Ten Kao Yuan | Student name | Student name | Student name | ||||||||||||
| Group 6 | HE Lingfei | MAO Chenxin | WANG Yingbei | |||||||||||||||
| Trenchcoat Detectives | Anuthama Murugesan | Krutika Balveer Choudhary | Sumalika Kodumuru | Student name | Student name | Student name | ||||||||||||
| theArules | Cao Bo | Guan Yifei | Zhou Yuhui | |||||||||||||||
| The Indian Story | Luo Mandi | Sandhya Vasudeva Rao | Priyadarshini Majumdar | Ghost | Ghost | Ghost | ||||||||||||
| visualizeR | Eric Prabowo | Asmit Adgaonkar | Shuo Zhang | - | - | - | ||||||||||||
| Group11 TripleY | Wei Yunna | Chen Yin Jue | Xu Yue | -- | -- | -- | ||||||||||||
| Group 12 | Arunkumar Chavarukulangara Rajan | Josef Carlo Exconde | Sandeep Chala | -- | -- | -- | ||||||||||||
| Your Team name | Student name | Student name | Student name | Student name | Student name | Student name | ||||||||||||
| Your Team name | Student name | Student name | Student name | Student name | Student name | Student name | ||||||||||||
| Group 15: Characterising Pandemic Spread Using R | Chua Gim Hong | Huang Liwei | Ngo Siew Hui | -- | -- | -- | ||||||||||||
| Group 16 | Jiaqi Zhang | Xintian Liu | Hongjun Qian | Student name | Student name | Student name | ||||||||||||
| Your Team name | Student name | Student name | Student name | Student name | Student name | Student name | ||||||||||||
| Group 18 - Intelligent Airlines Network | Debasish Behera | Manish Mittal | Roger Ganga Sundaraj | Student name | Student name | Student name | ||||||||||||
| Group 13 | Rishi Tandon | - | - | - | - | - | ||||||||||||
