Difference between revisions of "ISSS608 2016-17 T3 Assign ONG GUAN JIE JASON"

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<font size = 5; color="#FFFFFF">ISSS608 Assignment 2 Ong Guan Jie Jason </font>
 
<font size = 5; color="#FFFFFF">ISSS608 Assignment 2 Ong Guan Jie Jason </font>
 
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[[ISSS608_2016-17_T3_Assign_ONG_GUAN_JIE_JASON| <font color="#FFFFFF">Background</font>]]
 
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<br/>
  
<font size="5">'''To be a Visual Detective'''</font>
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<font size="5">'''Mini-Challenge 2'''</font>
  
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.
+
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?
  
The assignment topics are based on VAST Challenge 2017.  You are required to choose one of the challenge topic provided below and work out the solution. 
+
=Prelude=
 
 
=Overview=
 
  
 
Mistford is a mid-size city is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors.  Mitch Vogel is a post-doc student studying ornithology at Mistford College and has been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, is decreasing! The decrease is sufficiently significant that the Pangera Ornithology Conservation Society is sponsoring Mitch to undertake additional studies to identify the possible reasons. Mitch is gaining access to several datasets that may help him in his work, and he has asked you (and your colleagues) as experts in visual analytics to help him analyze these datasets.
 
Mistford is a mid-size city is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors.  Mitch Vogel is a post-doc student studying ornithology at Mistford College and has been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, is decreasing! The decrease is sufficiently significant that the Pangera Ornithology Conservation Society is sponsoring Mitch to undertake additional studies to identify the possible reasons. Mitch is gaining access to several datasets that may help him in his work, and he has asked you (and your colleagues) as experts in visual analytics to help him analyze these datasets.
  
==Mini-Challenge 1==
 
The Boonsong Lekagul Nature Preserve is used by local residents and tourists for day-trips, overnight camping or sometimes just passing through to access main thoroughfares on the opposite sides of the preserve.  The entrance booths of the preserve are monitored in order to generate revenue as well as monitor usage.  Vehicles entering and exiting the preserve must pay a fee based on their number of axles (personal auto, recreational trailer, semi-trailer, etc.).  This generates a data stream with entry/exit timestamps and vehicle type. There are also other locations in the part that register traffic passing through. While hiking through the various parts of the preserve, Mitch has noticed some odd behaviors of vehicles that he doesn’t think are consistent with the kinds of park visitors he would expect. If there were some way that Mitch could analyze the behaviors of vehicles through the park over time, this may assist him in his investigations.
 
  
Please visit [http://vacommunity.org/VAST+Challenge+2017+MC1 VAST Challenge 2017: Mini-Challenge 1] for more information and to download the data.
+
=Overview=
  
==Mini-Challenge 2==
+
Ornithology student Mitch Vogel was immediately suspicious of the noxious gases just pouring out of the smokestacks from the four manufacturing factories south of the nature preserve. He was almost certain that all of these companies are contributing to the downfall of the poor Rose-crested Blue Pipit bird. But when he talked to company representatives and workers, they all seem to be nice people and actually pretty respectful of the environment.
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?
 
 
 
Please visit [http://vacommunity.org/VAST+Challenge+2017+MC2 VAST Challenge 2017: Mini-Challenge 2].
 
 
 
==Mini-Challenge 3==
 
As Mitch works independently, he realizes that he cannot continually visit all areas of the preserve to inspect for environmental impacts as well as he would like to. He realizes that his analysis would be incomplete without thorough surveillance and knowledge of the preserve health over time. Fortunately, Mitch has acquired data from some commercial multi-spectral imagers that have been routinely covering the nature preserve every few weeks. Mitch believes that a visual analytics approach can help him achieve an understanding of the preserve health and alert him to possible conditions that may be impacting his birds.
 
 
 
Please visit [http://vacommunity.org/VAST+Challenge+2017+MC3 VAST Challenge 2017: Mini-Challenge 3] for more information and to download the data.
 
 
 
==Grand Challenge==
 
Mitch realizes that explorations into each of these three areas (covered by the mini-challenges) will reveal important, enlightening information. However, could there be relationships among discoveries made across two or even all of the investigations that could reveal even more about what is happening across the nature preserve and how it is happening. Mitch remembers that you mentioned to him how important it is to analyze not only what is happening, but the entire range of “who-what-where-why-when- and –how”. This understanding will enable him to pursue positive steps in helping to save the Rose-Crested Blue Pipit.
 
 
 
Please visit [http://vacommunity.org/VAST+Challenge+2017+Grand+Challenge VAST Challenge 2017: Grand Challenge] for more information and to download the data.
 
  
 +
In fact, Mitch was surprised to learn that the factories had recently taken steps to make their processes more environmentally friendly, even though it raised their cost of production. Mitch discovered that the state government has been monitoring the gaseous effluents from the factories through a set of sensors, distributed around the factories, and set between the smokestacks, the city of Mistford and the nature preserve. The state has given Mitch access to their air sampler data, meteorological data, and locations map. Mitch is very good in Excel, but he knows that there are better tools for data discovery, and he knows that you are very clever at visual analytics and would be able to help perform an analysis.
  
=Visualisation Software=
+
Mini-Challenge 2 provides a three month set of data for you to analyze, covering April, August, and December 2016.
  
To perform the visual analysis, students are encouraged to explore any one or a combination of the following software:
+
==Challenge==
*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.
+
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. In addition, prepare a video that shows how you used visual analytics to solve this challenge. Novel visualizations and analysis approaches are especially interesting for this mini-challenge. Please do not use any other data in your work (including other Internet-based sources or other mini-challenge data).
  
 +
==Questions==
  
=Submission details=
+
# 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.
This is an individual assignment. You are required to work on the assignment and prepare submission individually. Your completed assignment is due on '''7th July 2017, by 11.59pm mid-night'''.
+
# 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.
 
 
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: ISS608_2016-17_T3_Assign_FullName.
 
 
 
The assignment wiki page should include the URL link to the web-based interactive data visualization system prepared.
 
  
  
 
=Reference=
 
=Reference=
  
==Past assignment by ISSS608 students==
+
Please visit [http://vacommunity.org/VAST+Challenge+2017+MC2 VAST Challenge 2017: Mini-Challenge 2].
* [https://wiki.smu.edu.sg/1617t1ISSS608g1/ISSS608_2016-17_T1_Assign3_Ong_Han_Ying ISSS608_2016-17_T1_Assign3_Ong_Han_Ying]
 
  
==Past assignment by IS428 students==
 
* [https://wiki.smu.edu.sg/1617t1IS428g1/IS428_2016-17_Term1_Assign3_Gwendoline_Tan_Wan_Xin IS428 2016-17 Term1 Assign3 Gwendoline Tan Wan Xin]
 
* [https://wiki.smu.edu.sg/1617t1IS428g1/IS428_2016-17_Term1_Assign3_Lim_Kim_Yong IS428 2016-17 Term1 Assign3 Lim Kim Yong]
 
* [https://wiki.smu.edu.sg/1617t1IS428g1/IS428_2016-17_Term1_Assign3_Tan_Kee_Hock IS428 2016-17 Term1 Assign3 Tan Kee Hock]
 
  
 +
=Acknowledgement=
  
=Assignment Q&A=
+
<p>
 +
This assignment will not have been possible if not for the unwavering support of Prof Kam Tin Seong.<br>
 +
Also, I will like to take this opportunity to thank Yale Zhang for his help in improving the windrose plot for me. I really appreciate it.<br>
 +
Lastly, do visit and support the work of my awesome and talented teammates! :)
 +
</p>
  
Need more clarification, please feel free to pen down your questions.
+
[https://wiki.smu.edu.sg/1617t3isss608g1/ISSS608_2016-17_T3_Assign_KISHAN_BHARADWAJ_SHRIDHAR Kishan Bharadwaj Shridhar]<br>
 +
[https://wiki.smu.edu.sg/1617t3isss608g1/ISSS608_2016-17_T3_Assign_ZHANG_YANRONG Zhang Yanrong]<br>

Latest revision as of 12:09, 12 July 2017

JO Smokestack.jpg ISSS608 Assignment 2 Ong Guan Jie Jason

Background

Data Preparation

Visualization

Observations & Insights

Conclusion

Comments

 


Mini-Challenge 2

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?

Prelude

Mistford is a mid-size city is located to the southwest of a large nature preserve. The city has a small industrial area with four light-manufacturing endeavors. Mitch Vogel is a post-doc student studying ornithology at Mistford College and has been discovering signs that the number of nesting pairs of the Rose-Crested Blue Pipit, a popular local bird due to its attractive plumage and pleasant songs, is decreasing! The decrease is sufficiently significant that the Pangera Ornithology Conservation Society is sponsoring Mitch to undertake additional studies to identify the possible reasons. Mitch is gaining access to several datasets that may help him in his work, and he has asked you (and your colleagues) as experts in visual analytics to help him analyze these datasets.


Overview

Ornithology student Mitch Vogel was immediately suspicious of the noxious gases just pouring out of the smokestacks from the four manufacturing factories south of the nature preserve. He was almost certain that all of these companies are contributing to the downfall of the poor Rose-crested Blue Pipit bird. But when he talked to company representatives and workers, they all seem to be nice people and actually pretty respectful of the environment.

In fact, Mitch was surprised to learn that the factories had recently taken steps to make their processes more environmentally friendly, even though it raised their cost of production. Mitch discovered that the state government has been monitoring the gaseous effluents from the factories through a set of sensors, distributed around the factories, and set between the smokestacks, the city of Mistford and the nature preserve. The state has given Mitch access to their air sampler data, meteorological data, and locations map. Mitch is very good in Excel, but he knows that there are better tools for data discovery, and he knows that you are very clever at visual analytics and would be able to help perform an analysis.

Mini-Challenge 2 provides a three month set of data for you to analyze, covering April, August, and December 2016.

Challenge

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. In addition, prepare a video that shows how you used visual analytics to solve this challenge. Novel visualizations and analysis approaches are especially interesting for this mini-challenge. Please do not use any other data in your work (including other Internet-based sources or other mini-challenge data).

Questions

  1. 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.
  2. 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.
  3. 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.


Reference

Please visit VAST Challenge 2017: Mini-Challenge 2.


Acknowledgement

This assignment will not have been possible if not for the unwavering support of Prof Kam Tin Seong.
Also, I will like to take this opportunity to thank Yale Zhang for his help in improving the windrose plot for me. I really appreciate it.
Lastly, do visit and support the work of my awesome and talented teammates! :)

Kishan Bharadwaj Shridhar
Zhang Yanrong