Difference between revisions of "Assignments"

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<font size = 5; color="#FFFFFF">IS428 Visual Analytics for Business Intelligenceand Applications </font>
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=Overview=
 
=Overview=
  
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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. 
  
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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.
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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).
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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=
  
==General task==
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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. 
The four factories in the industrial area are subjected to higher-than-usual environmental assessment, due to their proximity to both the city and the preserve. Gaseous effluent data from several sampling stations has been collected over several months, along with meteorological data (wind speed and direction), that could help Mitch understand what impact these factories may be having on the Rose-Crested Blue Pipit. These factories are supposed to be quite compliant with recent years’ environmental regulations, but Mitch has his doubts that the actual data has been closely reviewed. Could visual analytics help him understand the real situation?
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==Task 1: Spatio-temporal Analysis of Official Air Quality==
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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?
  
The primary job for Mitch is to determine which (if any) of the factories may be contributing to the problems of the Rose-crested Blue Pipit. Often, air sampling analysis deals with a single chemical being emitted by a single factory. In this case, though, there are four factories, potentially each emitting four chemicals, being monitored by nine different sensors. Further, some chemicals being emitted are more hazardous than others. Your task, as supported by visual analytics that you apply, is to detangle the data to help Mitch determine where problems may be. Use visual analytics to analyze the available data and develop responses to the questions below.
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Your submission for this questions should contain no more than 10 images and 1000 words.
  
==The specific tasks==
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==Task 2: Spatio-temporal Analysis of Citizen Science Air Quality Measurements ==
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Using appropriate data visualisation, you are required will be asked to answer the following types of questions:
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* 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.
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* 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.
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 +
==Task 3==
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Urban air pollution is a complex issue.  There are many factors affecting the air quality of a city.  Some of the possible causes are:
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* 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. 
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* Local meteorology such as temperature, pressure, rainfall, humidity, wind etc
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* Local topography
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* Complex interactions between local topography and meteorological characteristics.
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* Transboundary pollution for example the haze that intruded into Singapore from our neighbours.
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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. 
  
* Characterize the sensors’ performance and operation. 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 9 images and 1000 words.
 
* Now turn your attention to the chemicals themselves. Which chemicals are being detected by the sensor group? What patterns of chemical releases do you see, as being reported in the data? Limit your response to no more than 6 images and 500 words.
 
* Which factories are responsible for which chemical releases? Carefully describe how you determined this using all the data you have available. For the factories you identified, describe any observed patterns of operation revealed in the data. Limit your response to no more than 8 images and 1000 words.
 
  
 
=The Data Sets=
 
=The Data Sets=
  
The major data sets are provided for this assignment, they are:  
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Four major data sets in zipped file format are provided for this assignment, they are:  
  
* Official air quality measurements (5 stations in the city) – as per EU guidelines on air quality monitoring see the data description [https://drive.google.com/file/d/1v5yCL-LdriDwa65qXPbFL7b0tydylDlb/view HERE…]
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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, incl. temperature, humidity and pressure (many stations) and topography (gridded data).  
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* Citizen science air quality measurements (Air Tube.zip) , incl. temperature, humidity and pressure (many stations) and topography (gridded data).  
* Meteorological measurements (1 station): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility
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* Meteorological measurements (1 station)(METEO-data.zip): Temperature; Humidity; Wind speed; Pressure; Rainfall; Visibility
* Topography data
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* 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].
 
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 '''8th October 2017, by 11.59pm mid-night'''.
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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_2017-18_T1_Assign_FullName.
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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

Va.jpg IS428 Visual Analytics for Business Intelligence

About

Assignment Dropbox

 


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.

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


Assignment Q&A

Need more clarification, please feel free to pen down your questions.