Difference between revisions of "Assignments"
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| − | <font size = 5; color="#FFFFFF">IS428 Visual Analytics for Business | + | <font size = 5; color="#FFFFFF">IS428 Visual Analytics for Business Intelligence </font> |
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=Overview= | =Overview= | ||
| + | Air pollution is an important risk factor for health in Europe and worldwide. A recent review of the global burden of disease showed that it is one of the top ten risk factors for health globally. Worldwide an estimated 7 million people died prematurely because of pollution; in the European Union (EU) 400,000 people suffer a premature death. The Organisation for Economic Cooperation and Development (OECD) predicts that in 2050 outdoor air pollution will be the top cause of environmentally related deaths worldwide. In addition, air pollution has also been classified as the leading environmental cause of cancer. | ||
| + | Air quality in Bulgaria is a big concern: measurements show that citizens all over the country breathe in air that is considered harmful to health. For example, concentrations of PM2.5 and PM10 are much higher than what the EU and the World Health Organization (WHO) have set to protect health. | ||
| + | |||
| + | Bulgaria had the highest PM2.5 concentrations of all EU-28 member states in urban areas over a three-year average. For PM10, Bulgaria is also leading on the top polluted countries with 77 μg/m3on the daily mean concentration (EU limit value is 50 μg/m3). | ||
| + | |||
| + | According to the WHO, 60 percent of the urban population in Bulgaria is exposed to dangerous (unhealthy) levels of particulate matter (PM10). | ||
=The Task= | =The Task= | ||
| − | + | In this assignment, you are required to use visual analytics approach to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern. | |
| − | |||
| − | + | ==Task 1: Spatio-temporal Analysis of Official Air Quality== | |
| − | + | Characterize the past and most recent situation with respect to air quality measures in Sofia City. What does a typical day look like for Sofia city? Do you see any trends of possible interest in this investigation? What anomalies do you find in the official air quality dataset? How do these affect your analysis of potential problems to the environment? | |
| − | + | Your submission for this questions should contain no more than 10 images and 1000 words. | |
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| − | = | + | ==Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements == |
| + | |||
| + | Using appropriate data visualisation, you are required will be asked to answer the following types of questions: | ||
| + | |||
| + | * Characterize the sensors’ coverage, performance and operation. Are they well distributed over the entire city? Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture? Limit your response to no more than 4 images and 600 words. | ||
| + | * Now turn your attention to the air pollution measurements themselves. Which part of the city shows relatively higher readings than others? Are these differences time dependent? Limit your response to no more than 6 images and 800 words. | ||
| + | |||
| + | ==Task 3== | ||
| + | |||
| + | Urban air pollution is a complex issue. There are many factors affecting the air quality of a city. Some of the possible causes are: | ||
| + | |||
| + | * Local energy sources. For example, according to [http://unmaskmycity.org/project/sofia/ Unmask My City], a global initiative by doctors, nurses, public health practitioners, and allied health professionals dedicated to improving air quality and reducing emissions in our cities, Bulgaria’s main sources of PM10, and fine particle pollution PM2.5 (particles 2.5 microns or smaller) are household burning of fossil fuels or biomass, and transport. | ||
| + | * Local meteorology such as temperature, pressure, rainfall, humidity, wind etc | ||
| + | * Local topography | ||
| + | * Complex interactions between local topography and meteorological characteristics. | ||
| + | * Transboundary pollution for example the haze that intruded into Singapore from our neighbours. | ||
| − | + | In this third task, you are required to reveal the relationships between the factors mentioned above and the air quality measure detected in Task 1 and Task 2. Limit your response to no more than 5 images and 600 words. | |
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| − | + | =The Data Sets= | |
| − | + | Four major data sets in zipped file format are provided for this assignment, they are: | |
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| − | + | * Official air quality measurements (5 stations in the city)(EEA Data.zip) – as per EU guidelines on air quality monitoring see the data description [https://drive.google.com/file/d/1v5yCL-LdriDwa65qXPbFL7b0tydylDlb/view HERE…] | |
| + | * Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data). | ||
| + | * Meteorological measurements (1 station)(METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility | ||
| + | * Topography data (TOPO-DATA) | ||
| + | They can be download by click on this [https://storage.cloud.google.com/global-datathon-2018/sofia-air/air-sofia.zip link]. | ||
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=Submission details= | =Submission details= | ||
| − | This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on ''' | + | This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on '''11th November 2018, by 11.59pm mid-night'''. |
| − | You need to edit your assignment in the appropriate wiki page of the Assignment Dropbox. The title of the wiki page should be in the form of: | + | You need to edit your assignment in the appropriate wiki page of the Assignment Dropbox. The title of the wiki page should be in the form of: IS428_2018-19_T1_Assign_FullName. |
The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared. | The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared. | ||
Latest revision as of 08:18, 2 November 2018
IS428 Visual Analytics for Business Intelligence
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To be a Visual Detective
The assignments require you to put the concepts, methods and techniques you had learned in class to solve real world problem using visual analytics techniques. Students should also use the assignments to gain hands-on experience on using the data visualisation toolkits I had shared with you to complate the assignment.
Contents
Overview
Air pollution is an important risk factor for health in Europe and worldwide. A recent review of the global burden of disease showed that it is one of the top ten risk factors for health globally. Worldwide an estimated 7 million people died prematurely because of pollution; in the European Union (EU) 400,000 people suffer a premature death. The Organisation for Economic Cooperation and Development (OECD) predicts that in 2050 outdoor air pollution will be the top cause of environmentally related deaths worldwide. In addition, air pollution has also been classified as the leading environmental cause of cancer.
Air quality in Bulgaria is a big concern: measurements show that citizens all over the country breathe in air that is considered harmful to health. For example, concentrations of PM2.5 and PM10 are much higher than what the EU and the World Health Organization (WHO) have set to protect health.
Bulgaria had the highest PM2.5 concentrations of all EU-28 member states in urban areas over a three-year average. For PM10, Bulgaria is also leading on the top polluted countries with 77 μg/m3on the daily mean concentration (EU limit value is 50 μg/m3).
According to the WHO, 60 percent of the urban population in Bulgaria is exposed to dangerous (unhealthy) levels of particulate matter (PM10).
The Task
In this assignment, you are required to use visual analytics approach to reveal spatio-temporal patterns of air quality in Sofia City and to identify issues of concern.
Task 1: Spatio-temporal Analysis of Official Air Quality
Characterize the past and most recent situation with respect to air quality measures in Sofia City. What does a typical day look like for Sofia city? Do you see any trends of possible interest in this investigation? What anomalies do you find in the official air quality dataset? How do these affect your analysis of potential problems to the environment?
Your submission for this questions should contain no more than 10 images and 1000 words.
Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements
Using appropriate data visualisation, you are required will be asked to answer the following types of questions:
- Characterize the sensors’ coverage, performance and operation. Are they well distributed over the entire city? Are they all working properly at all times? Can you detect any unexpected behaviors of the sensors through analyzing the readings they capture? Limit your response to no more than 4 images and 600 words.
- Now turn your attention to the air pollution measurements themselves. Which part of the city shows relatively higher readings than others? Are these differences time dependent? Limit your response to no more than 6 images and 800 words.
Task 3
Urban air pollution is a complex issue. There are many factors affecting the air quality of a city. Some of the possible causes are:
- Local energy sources. For example, according to Unmask My City, a global initiative by doctors, nurses, public health practitioners, and allied health professionals dedicated to improving air quality and reducing emissions in our cities, Bulgaria’s main sources of PM10, and fine particle pollution PM2.5 (particles 2.5 microns or smaller) are household burning of fossil fuels or biomass, and transport.
- Local meteorology such as temperature, pressure, rainfall, humidity, wind etc
- Local topography
- Complex interactions between local topography and meteorological characteristics.
- Transboundary pollution for example the haze that intruded into Singapore from our neighbours.
In this third task, you are required to reveal the relationships between the factors mentioned above and the air quality measure detected in Task 1 and Task 2. Limit your response to no more than 5 images and 600 words.
The Data Sets
Four major data sets in zipped file format are provided for this assignment, they are:
- Official air quality measurements (5 stations in the city)(EEA Data.zip) – as per EU guidelines on air quality monitoring see the data description HERE…
- Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data).
- Meteorological measurements (1 station)(METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility
- Topography data (TOPO-DATA)
They can be download by click on this link.
Visualisation Software
To perform the visual analysis, students are encouraged to explore any one or a combination of the following software:
- Tableau
- JMP Pro
- Qlik Sense
- Microsoft Power BI
One of the goals of this assignment is for you to learn to use and evaluate the effectiveness of these visual analytics tools.
Submission details
This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on 11th November 2018, by 11.59pm mid-night.
You need to edit your assignment in the appropriate wiki page of the Assignment Dropbox. The title of the wiki page should be in the form of: IS428_2018-19_T1_Assign_FullName.
The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared.
Reference
- IS428 2016-17 Term1 Assign3 Gwendoline Tan Wan Xin
- IS428 2016-17 Term1 Assign3 Lim Kim Yong
- IS428 2016-17 Term1 Assign3 Tan Kee Hock
Assignment Q&A
Need more clarification, please feel free to pen down your questions.
