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<font size = 5; color="#001a66"><span style="font-family:Century Gothic;">ISSS608: Visual Analytics and Applications</span></font>
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<font size = 5; color="#001a66"><span style="font-family:Century Gothic;">VAST CHALLENGE 2017 </span></font>
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<font size = 4; color="#001a66"><span style="font-family:Century Gothic;"> '''- SUMALIKA KODUMURU''' </span></font>
  
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<font size = 5; color="#ffffff">ISSS608 Visual Analytics and Applications</font>
 
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[[About| <font color="#FFFFFF">About</font>]]
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[[ISSS608 2016-17 T3 Assign SUMALIKA KODUMURU | <font color="#FFFFFF">Assignment Overview</font>]]
  
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[[ISSS608 2016-17 T3 Assign SUMALIKA KODUMURU| <font color="#FFFFFF"> Sensor Performance </font>]]
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[[Data Overview| <font color="#FFFFFF"> Data Overview </font>]]
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[[Question1_SUMALIKA KODUMURU| <font color="#FFFFFF"> Sensor Performance </font>]]
  
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[[Q2| <font color="#FFFFFF"> Patterns of Chemical Release </font>]]
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[[Question 2_SUMALIKA KODUMURU| <font color="#FFFFFF"> Patterns of Chemical Release </font>]]
  
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[[Q3| <font color="#FFFFFF"> Factories Responsible </font>]]
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[[Question 3_SUMALIKA KODUMURU| <font color="#FFFFFF"> Factories Responsible </font>]]
  
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[[References & Feedback | <font color="#FFFFFF"> References & Feedback </font>]]
 
[[References & Feedback | <font color="#FFFFFF"> References & Feedback </font>]]
  
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<font size="5">'''The Curious Case of Rose-Crested Blue Pipit'''</font>
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<font size = 5; color="#001a66"><span style="font-family:Century Gothic;"> '''Mystery at the Wildlife Preserve'''</span></font>
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[[File:Vast1.jpg|600px|center|float]]
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=Question1=
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<font size = 4; color="#001a66"><span style="font-family:Century Gothic;">'''The Challenge Overview:'''</span> </font>
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
 
 
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[[File:Sumalika_Q1P11.jpg|900px|center|float]]
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Mistford is a mid-size city 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.
  
 
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All the sensors need to capture the chemical readings at all times of the day for all the three months i.e. July, August and December.The "Calendar Plot" has dates highlighted in red indicating the days when sensors ( all 9) have failed to capture chemical readings. For example: On 2nd and 6th of April, 2nd, 4th and 7th of August and 2nd and 7th of December sensors have failed to capture the readings. Further investigation needs to be performed to make a deduction on sensor readings. At this point the sensors could have
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<font size = 4; color="#001a66"><span style="font-family:Century Gothic;">'''The Mini Challenge 2 Overview:'''</span> </font>
 
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- Incorrectly captured data
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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.
 
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- Missed capturing data
 
[[File:Sumalika_Q1P2.jpg|900px|center|float]]
 
 
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To identify the missing data, drill down to "Hour" level to note the monitors/sensors that are responsible for these readings:
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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.
On 2nd April and 6th April, all the sensors recorded no readings at 12 AM. Either the factories were not working or have started late than their usual time and hence readings were not recorded. But when compared to the other days in this month, rest of the days have readings captured even at 12 AM and as there is no evident pattern in the operational hours of the factories,we can conclude that the sensors were not functioning well in capturing the readings on 2nd and 6th April.  
 
 
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[[File:Sumalika_Q1P5.jpg|900px|center|float]]
 
 
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Similar to the above case in April month, on the 4th and 7th August all the sensors recorded no readings at 12 AM. However on that day at 12 AM Monitor 3 recorded activity, but instead of 4 chemicals it captured the release of two chemicals. On further investigation it was observed that AGOG-3A and Methylosmolene were the chemicals that released from factories.  
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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)
 
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This finding raises several questions such as - Were factories operating on 2nd August at 12 AM? If no then why do we see these readings?, did the sensor capture it incorrectly ? or were there any suspicious activities? Before making any conclusions, behavior of the readings needs to be analysed and hence December readings are also considered to see possible similar patterns.
 
 
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[[File:Sumalika_Q1P6.jpg|900px|center|float]]
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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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Similar to the previous months, the sensors did not capture chemicals on all days at all times. On the 2nd and 7th of December, sensors missed to read chemicals at 12 AM. On further analysis it can be seen that Monitor No: 6,7,8 show readings but not all the four chemicals. Further analysis needs to be performed on the chemicals released on these particular days and identify a pattern. Overall view of how the sensors have captured the data on each day can be seen in Calendar Plot below.
 
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[[File:Sumalika_Q1P8.PNG|450px|right|float]]
 
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Now that we identified missing data we need to check if there were any incorrectly captured data. With the help of a Heat Map it can be evidently deduced that sensors captured more of AGOG-3A and less of Methylosmolene. Two questions arise at this point:
 
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1. Did the sensors capture the chemicals correctly?
 
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2. Was there excess release of a certain chemical from a factory?
 
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[[File:Sumalika_Q1P9_(2).jpg|1200px|center|float]]
 
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Two deductions can be made from the above graph:
 
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1. Apart from the days recognized above with missing data, there are other days in the month with inconsistent readings. Chemicals " Appluimonia" and " Cholorodinine" were captured consistently by the sensors and inconsistency is seen for the other two chemicals.
 
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2. Every time there is an increase in the number of readings for AGOG-3A there is a decrease in the number of readings for Methylosmolene. This is seen clearly in the graph below.
 
 
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[[File:Sumalika_Q1P10.jpg|600px|center|float]]
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<font size = 4; color="#001a66"><span style="font-family:Century Gothic;">''' Questions: '''</span> </font>
 
<br/>
 
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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.
 
<br/>
 
<br/>
Further investigation needs to be performed on the sensor readings for each chemical to see if there was an excess release of a certain chemical.  
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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.
 
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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

Latest revision as of 10:02, 17 July 2017

ISSS608: Visual Analytics and Applications
VAST CHALLENGE 2017
- SUMALIKA KODUMURU

Assignment Overview

Data Overview

Sensor Performance

Patterns of Chemical Release

Factories Responsible

References & Feedback

 


Mystery at the Wildlife Preserve

float


The Challenge Overview:
Mistford is a mid-size city 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.


The Mini Challenge 2 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.

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)

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?


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