Difference between revisions of "ISSS608 2016-17 T3 Assign NGO SIEW HUI"
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<font size="5">'''VAST Challenge 2017 - Mystery at the Wildlife Preserve'''</font> | <font size="5">'''VAST Challenge 2017 - Mystery at the Wildlife Preserve'''</font> |
Revision as of 15:43, 21 June 2017
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VAST Challenge 2017 - Mystery at the Wildlife Preserve
ISSS608 Visual Analytics and Applications - Individual Assignment
Prepared by Ngo Siew Hui
Contents
Background
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.
For full details, please visit VAST Challenge 2017: Overview.
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?
For more details on Mini-Challenge 2, please visit VAST Challenge 2017: Mini-Challenge 2.
Approach
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Data Preparation
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Visualisation
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Analysis
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Discussion
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References
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