Difference between revisions of "IS428 AY2019-20T1 Assign Foo Yong Long"

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[[File:MC1-2019.jpg|153px|left]]
 
 
<b><font size = 6; color="#43464b"> VAST Challenge 2019 Mini-Challenge 1:<br>Crowdsourcing for Situational Awareness</font></b>
 
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[[IS428 AY2019-20T1 Assign Foo Yong Long|<b><font size="3"><font color="#43464b">Problem Description</font></font></b>]]
 
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Data Transformation|<b><font size="3"><font color="#43464b">Data Transformation</font></font></b>]]
 
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Radiation Measurements Over time|<b><font size="3"><font color="#43464b">Radiation Over Time</font></font></b>]]
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[[IS428 AY2019-20T1 Assign Foo Yong Long|<font color="#000000" size=2><b>OVERVIEW</b></font>]]
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Uncertainity| <b><font size="3"><font color="#43464b">Uncertainty</font></font></b>]]
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Data Transformation|<font color="#000000" size=2><b>DATA TRANSFORMATION</b></font>]]
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Scale of contamination| <b><font size="3"><font color="#43464b">Scale of contamination</font></font></b>]]
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[[IS428 AY2019-20T1 Assign Foo Yong Long_RiskAnalysis|<font color="#000000" size=2><b>RISKS</b></font>]]
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long_Summary| <b><font size="3"><font color="#43464b">Summary</font></font></b>]]
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[[IS428 AY2019-20T1 Assign Foo Yong Long:R&R|<font color="#000000" size=2><b>RECOMMENDATION AND RATIONALE</b></font>]]
  
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[[IS428 AY2019-20T1 Assign Foo Yong Long: Visualization|<font color="#000000" size=2><b>VISUALIZATION</b></font>]]
 
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<font size="4"><font color="#43464b">'''Visualization Goals'''</font></font>
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1) Understanding the risks involved
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2) Help the public better understand conditions in the city
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3) Recommending a course of action for the government to mitigate risks
  
  
 
<font size="4"><font color="#43464b">'''Overview'''</font></font>
 
<font size="4"><font color="#43464b">'''Overview'''</font></font>
  
St. Himark is a vibrant community located in the Oceanus Sea. Home to the world-renowned St. Himark Museum, beautiful beaches, and the Wilson Forest Nature Preserve, St. Himark is one of the region’s best cities for raising a family and provides employment across a number of industries including the Always Safe Nuclear Power Plant. Well, all that was true before the disastrous earthquake that hits the area during the course of this year’s challenge. Mayor Jordan, city officials, and emergency services are overwhelmed and are desperate for assistance in understanding the true situation on the ground and how best to deploy the limited resources available to this relatively small community.
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A vibrant community to 246,839 people, St.Himark consists of some of the best cultural attractions and is one of the region's best places to raise children. Bustling with economic activity, it is really accessible thanks to five bridges and one highway that connect the city to the mainland.
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<font size="4"><font color="#43464b">'''Problem and Motivation'''</font></font>
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The Always Safe nuclear plant, one of the city's largest employers, had been struck by an earthquake, resulting in a leak of radioactive contamination. Furthermore, a coolant leak has sprayed employees' cars and contaminated them at varying levels. Now, the city’s government and emergency management officials are trying to understand if there is a risk to the public while also responding to other emerging crises related to the earthquake as well as satisfying the public’s concern over radiation.
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<font size="4"><font color="#43464b">'''Dataset'''</font></font>
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1)Static Sensor Data
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The government has deployed operated stationary monitors with data from citizen-operated mobile sensors to help them better understand conditions in the city and identify likely locations that will require further monitoring, cleanup, or even evacuation.
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2)Mobile Sensor Data
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Thanks to a group of citizen scientists led by the members of the Himark Science Society, lower-cost homemade sensors are deployed to citizens, including employees of Always Safe nuclear power plant. These sensors are attached to their cars 
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<font size="4"><font color="#43464b">'''Task and Questions'''</font></font>
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The visualization has been grouped into '''6''' portions including this page as follows;
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'''1) Overview'''
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Background information and summary of the problem on hand
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'''2) Data transformation'''
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Data preparation process
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'''3) Risks'''
  
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a) Visualize radiation measurements over time from both static and mobile sensors to identify areas where radiation over background is detected. Characterize changes over time.
  
<font size="4"><font color="#43464b">'''Problem and Motivation'''</font></font><br>
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b) Use visual analytics to represent and analyze uncertainty in the measurement of radiation across the city.
  
St. Himark has been hit by an earthquake, leaving officials scrambling to determine the extent of the damage and dispatch limited resources to the areas in most need. They quickly receive seismic readings and use those for an initial deployment but realize they need more information to make sure they have a realistic understanding of the true conditions throughout the city.
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Compare the uncertainty of the static sensors to the mobile sensors. What anomalies can you see? Are there sensors that are too uncertain to trust?
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Which regions of the city have greater uncertainty of radiation measurement? Use visual analytics to explain your rationale.
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What effects do you see in the sensor readings after the earthquake and other major events? What effect do these events have on uncertainty?
  
In a prescient move, the city of St. Himark released a new damage reporting mobile application shortly before the earthquake. This app allows citizens to provide more timely information to the city to help them understand damage and prioritize their response. In this mini-challenge, use app responses in conjunction with shake maps of the earthquake strength to identify areas of concern and advise emergency planners.
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c) Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern?
  
With emergency services stretched thin, officials are relying on citizens to provide them with much needed information about the effects of the quake to help focus recovery efforts.
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'''4) Recommendation and rationale'''
  
By combining seismic readings of the quake, responses from the app, and background knowledge of the city, help the city triage their efforts for rescue and recovery.
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Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city? Estimate how many cars may have been contaminated when coolant leaked from the Always Safe plant. Use visual analysis of radiation measurements to determine if any have left the area. Indicated where you would deploy more sensors to improve radiation monitoring in the city. Would you recommend more static sensors or more mobile sensors or both? Use your visualization of radiation measurement uncertainty to justify your recommendation.
  
Please visit [https://vast-challenge.github.io/2019/MC1.html VAST Challenge 2019: Mini-Challenge 1] for more information and to download the data.
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Summarize the state of radiation measurements at the end of the available period. Use your novel visualizations and analysis approaches to suggest a course of action for the city. Use visual analytics to compare the static sensor network to the mobile sensor network. What are the strengths and weaknesses of each approach? How do they support each other?
  
<font size="2"><font color="#43464b">'''Tasks and Questions'''</font></font><br>
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The data for this challenge can be analyzed either as a static collection or as a dynamic stream of data, as it would occur in a real emergency. Describe how you analyzed the data - as a static collection or a stream. How do you think this choice affected your analysis? Limit your response to 200 words and 3 images.
  
# Emergency responders will base their initial response on the earthquake shake map. Use visual analytics to determine how their response should change based on damage reports from citizens on the ground. How would you prioritize neighborhoods for response? Which parts of the city are hardest hit? Limit your response to 1000 words and 10 images.
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'''5) Visualization'''
# Use visual analytics to show uncertainty in the data. Compare the reliability of neighborhood reports. Which neighborhoods are providing reliable reports? Provide a rationale for your response. Limit your response to 1000 words and 10 images.
 
# How do conditions change over time? How does uncertainty in change over time? Describe the key changes you see. Limit your response to 500 words and 8 images.
 
  
==Mini Challenge 1 Background==
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Visual guide on the storyboard
View the interactive Tableau design here: [Link to tableau dashboard]
 

Latest revision as of 05:21, 13 October 2019

Cover.png


OVERVIEW

DATA TRANSFORMATION

RISKS

RECOMMENDATION AND RATIONALE

VISUALIZATION



Visualization Goals

1) Understanding the risks involved

2) Help the public better understand conditions in the city

3) Recommending a course of action for the government to mitigate risks


Overview

A vibrant community to 246,839 people, St.Himark consists of some of the best cultural attractions and is one of the region's best places to raise children. Bustling with economic activity, it is really accessible thanks to five bridges and one highway that connect the city to the mainland.


Problem and Motivation

The Always Safe nuclear plant, one of the city's largest employers, had been struck by an earthquake, resulting in a leak of radioactive contamination. Furthermore, a coolant leak has sprayed employees' cars and contaminated them at varying levels. Now, the city’s government and emergency management officials are trying to understand if there is a risk to the public while also responding to other emerging crises related to the earthquake as well as satisfying the public’s concern over radiation.


Dataset

1)Static Sensor Data

The government has deployed operated stationary monitors with data from citizen-operated mobile sensors to help them better understand conditions in the city and identify likely locations that will require further monitoring, cleanup, or even evacuation.

2)Mobile Sensor Data

Thanks to a group of citizen scientists led by the members of the Himark Science Society, lower-cost homemade sensors are deployed to citizens, including employees of Always Safe nuclear power plant. These sensors are attached to their cars


Task and Questions

The visualization has been grouped into 6 portions including this page as follows;

1) Overview

Background information and summary of the problem on hand

2) Data transformation

Data preparation process

3) Risks

a) Visualize radiation measurements over time from both static and mobile sensors to identify areas where radiation over background is detected. Characterize changes over time.

b) Use visual analytics to represent and analyze uncertainty in the measurement of radiation across the city.

Compare the uncertainty of the static sensors to the mobile sensors. What anomalies can you see? Are there sensors that are too uncertain to trust? Which regions of the city have greater uncertainty of radiation measurement? Use visual analytics to explain your rationale. What effects do you see in the sensor readings after the earthquake and other major events? What effect do these events have on uncertainty?

c) Given the uncertainty you observed in question 2, are the radiation measurements reliable enough to locate areas of concern?

4) Recommendation and rationale

Highlight potential locations of contamination, including the locations of contaminated cars. Should St. Himark officials be worried about contaminated cars moving around the city? Estimate how many cars may have been contaminated when coolant leaked from the Always Safe plant. Use visual analysis of radiation measurements to determine if any have left the area. Indicated where you would deploy more sensors to improve radiation monitoring in the city. Would you recommend more static sensors or more mobile sensors or both? Use your visualization of radiation measurement uncertainty to justify your recommendation.

Summarize the state of radiation measurements at the end of the available period. Use your novel visualizations and analysis approaches to suggest a course of action for the city. Use visual analytics to compare the static sensor network to the mobile sensor network. What are the strengths and weaknesses of each approach? How do they support each other?

The data for this challenge can be analyzed either as a static collection or as a dynamic stream of data, as it would occur in a real emergency. Describe how you analyzed the data - as a static collection or a stream. How do you think this choice affected your analysis? Limit your response to 200 words and 3 images.

5) Visualization

Visual guide on the storyboard