Difference between revisions of "ISSS608 2017-18 T3 Assign Vishali Reddy Nalla"

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[[ISSS608_2016-17_T3_Assign_HUANG_LIWEI|<font color="#FFFFFF">Introduction</font>]]
 
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[[lw-questions|<font color="#FFFFFF">Data Preparation</font>]]
 
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[[lw-preparation|<font color="#FFFFFF">Data Visualisation & Analysis</font>]]
 
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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.<br>
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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?<br>
 
Please visit [http://vacommunity.org/VAST+Challenge+2017 VAST Challenge 2017] for more details.
 
 
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== Task ==
 
== Task ==
The primary job 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).<br>
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Please visit [http://vacommunity.org/VAST+Challenge+2017+MC2 Mini Challenge 2] for more details.
 
Please visit [http://vacommunity.org/VAST+Challenge+2017+MC2 Mini Challenge 2] for more details.

Revision as of 23:20, 21 June 2018

250px VAST Challenge 2018 - Mini Challenge 2

Presented by: Vishali Nalla  ([1])
Visualization tool: Tableau

Introduction

Data Preparation

Data Visualisation & Analysis

Comments


Overview

  500px

Task

Please visit Mini Challenge 2 for more details.