Difference between revisions of "ISSS608 2016-17 T3 Assign Jan Patrick Mabilangan Conclusion"
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<b><font size = 6> VAST Challenge 2018: Suspense at the Wildlife Preserve </font></b> | <b><font size = 6> VAST Challenge 2018: Suspense at the Wildlife Preserve </font></b> | ||
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+ | [[ISSS608_2017-18_T3_Assign_Jan_Patrick_Mabilangan_Gosioco|<b><font size="2">Background</font></b>]] | ||
+ | <br>[[ISSS608_2016-17_T3_Assign_Jan_Patrick_Mabilangan_Gosioco_Data_Prep|<b><font size="2">Data Preparation & Dashboard Design</font></b>]] | ||
+ | <br>[[ISSS608_2016-17_T3_Assign_Jan_Patrick_Mabilangan_Insight|<b><font size="2">Insights</font></b>]] | ||
+ | <br>[[ISSS608_2016-17_T3_Assign_Jan_Patrick_Mabilangan_Conclusion|<b><font size="2">Conclusion</font></b>]] | ||
==Conclusion== | ==Conclusion== |
Latest revision as of 12:49, 8 July 2018
Background
Data Preparation & Dashboard Design
Insights
Conclusion
Conclusion
Chemical Trends
We have seen the various trends of the different measures, locations, and values observed by the water sensor readings in the Boonsong Lekagul Wildlife Preserve.
For those identified as consistent or cyclical, the readings are more or less going to be around the average or predictable, so the Mistford College Hydrology Department will just have to monitor for any anomalies that will appear. This is made easier as such anomalies will become more apparent in reference to the already identified patterns. For measures that have only been observed to be present for some time or barely even there, attention must be brought to separate those that are insignificant to those that may truly link into instances of contamination.
We have also seen different chemical and location specific observations, highlighting incidences that suggest possibility of contamination on to the different waterways. These are areas of interest that can be studied further to learn root cause. Iron, Chromium, and Copper, to name a few, may be prioritized as these have had histories of reaching dangerous levels. Particularly, during the seemingly parkwide contamination that occurred in August 15, 2003, giving possible answer to what really happened around the date.
Dataset Anomalies
Several pitfalls in data collection have been shown to be present in the waterways samples dataset. Missing data in various instances and inconsistencies in the frequency of data collection all impede the comprehensive understanding of the potential problems to the environment and situation in the Preserve. Data not present for measures and locations make it insufficient to make comparisons and contrasts on values.
With all this, an improvement of the sampling strategy would certainly go a long way to help better our understanding. One such improvement would be to complete the data for the 3 identified locations that only have half as much readings as the rest, beginning only in 2009 while the rest have started in 1998. Generally increasing the amount and consistency of data collection to possibly daily would allow more accurate patterns to be discovered, eventually leading to predictive analysis.
Wildlife Hazard
Methylosmolene, the toxic chemical that is the subject of much controversy and primary piece of evidence against Kasios, had been gone from the soil, but has been detected in the waters of the Preserve. In the light of such discovery, it begs the question is this the same methylosmolene that had once been present in the soil? While the dataset alone cannot entirely answer this, investigation against Kasios for industrial waste dumping can once again continue, following the possibility that construction of the new ranger station had been a cover-up to dispose of the methylosmolene infused soil into the waterways.
Other wildlife hazards have also been revealed to be present, and with some guidance from the Water Quality Association International Headquarters and Laboratory, the Hydrology Department can continue to utilize the visualization to monitor safety level of chemicals in the water.
Finally, we saw how sampling strategy plays a key role in the detection of patterns and anomalies through the example of Somchair Methylosmolene values, with the current sampling method failing to capture the critical period before the spike. An improved sampling strategy that collects data daily would work hand-in-hand with the visual analysis, possibly revealing lifesaving information. For example, going back to the scenario above, had it been revealed by the daily data collection that in the period before the spike the increase was gradual, the Hydrology department would learn to know about the increasing trend through the dashboard, and they can address the concerns immediately. This increased frequency of information may mean the difference of sickness and health of an animal such as our beloved Pipit.