IS428 AY2019-20T1 Assign Ronald Lay Answers

VAST Challenge 2019: Mini-Challenge 1

Problem & Tasks

Data Transformation

Interactive Visualization

Answers

Q2: 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.

Missing reports among neighborhoods

Measure reliability among neighborhoods

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  Figure 2.1 - Overall intensity readings over time period

Based on Figure 2.1, there are 3 key analysis:

• Downtown, Northwest and Weston provide the most reliable reports among all the neighborhoods
• Wilson Forest provides the least reliable reports. Possible explanation could be Wilson Forest may experience power outage even before the major earthquake happens. However, there is no ongoing repair under Power current project.
• As highlighted in oval red, there are occasional periods where there are simply no reports. The possible cause may point to power/server outages

Delayed reports

Overall Delayed reports

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  Figure 2.2 - Delayed reporting

Power outages and other infrastructural problem result in delayed reports (Indicated by red ovals) and the server does not process the information until the power is restored. The explanation of number annotation is as followed:

• 1 & 2: It is noticeable the reported damage is on different timing. The timestamp is only recorded when the power is restored, resulting in an increase of the amount of damage reports from Thursday 3 to 5 PM due to accumulation of reports over the period of power outages.

Delayed reports by neighbourhood

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  Figure 2.3 - Delayed reporting per neighbour
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  Figure 2.4 - Medical reporting per neighbour

Based on the Figure 2.3, the highlighted red box shows there is indeed a sudden increase in number of reports posted on the server at the same time. Most of the neighbors are affected at some point of time, particularly Broadview, Chapparal, Old Town and Scenic Vista are the most vulnerable.
Using filter function to include only medical, the discovery led us to Figure 2.4, which shows 2 key analysis:

• The medical reports are mostly available between 8th at 8 PM to 11 PM and 9th at 3 PM to 7 PM for most of the neighborhoods.
• Cheddarford, Wilson Forest and Chapparal have the most amount of low density and missing reports across all the dates.

Variation on reported intensity and number of reports

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  Figure 2.5 - number of reports vs reported intensity

Based on figure 2.5, The reported intensity is highly varied across categories, which indicates there is a varying response among all the records and particularly medical is vulnerable to the reliability issue. It suggests the submitted records by the devices are of a little help in assessing damages over time as it only records in 5 minutes batch and as discussed earlier, power outages and other infrastructural damages highly impact the accuracy of intensity readings.

Q3: How do conditions change over time? How does uncertainty in data change over time? Describe the key changes you see.

Discrepancy in reported and shake intensity

Damage intensity versus Shake Intensity (Yellow line)

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  Figure 3.1 - Damage report vs shake intensity

Based on MC1 Data description, all the intensity are reported by people of St. Himark. However, there is a discrepancy between reported damage intensity and shake intensity, which leads to 2 possibilites:

• The reading of shake intensity can possibly be based on seismic monitor. It is explained by less variation on shake intensity (Refer to Figure 2.6) and significantly lower number of reports as seismic monitor or similar tools only reports to the server when they detect vibrations/shakes
• There is a difference in perceived feeling and actual view of damage. Based on figure 3.1, we can draw an insight that the actual view has more impact on our judgement, which can be explained by higher reported damage intensity.