This answer sheet should be used for your VAST
Challenge 2019 Mini-Challenge 2 submission. Please maintain the .htm format and
make sure that all hyperlinks are relative to the answer form.
Rename this form "index.htm" for your
submission. Remove these instructions
and any other example text below that is highlighted in yellow. Please see the
"Submission Instructions" at https://vast-challenge.github.io/2019/
for more detailed instructions.
Marion Smith, University of West Birmingham, smith@westbirmingham.ac.uk PRIMARY
Paul White, University of Northeastern Washington, white@unew.edu
Student Team: Please enter YES or NO
Provide
a list of tools used. Examples:
Tableau
Excel
Spinviz, developed by the University of West
Birmingham CS 459 Information Visualization class, taught Spring 2011 by Dr. Smith, and adapted by the student team
for the challenge.
Approximately how
many hours were spent working on this submission in total?
Provide
an estimate of the total number of hours worked on this submission by your
entire team.
May we post your
submission in the Visual Analytics Benchmark Repository after VAST Challenge
2019 is complete? Please
enter a YES or NO
Video
Provide
a link to your video. Example:
http://www.westbirmingham.ac.uk/uwb-smith-mc2-video.wmv
Questions
Your task, as supported by visual analytics that you apply,
is to help St. Himark's emergency management team
combine data from the government-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. Will data from citizen scientists clarify the
situation or make it more uncertain? Use visual analytics to develop responses
to the questions below. Novel visualizations of uncertainty are especially
interesting for this mini-challenge.
1 – Visualize radiation measurements over
time from both static and mobile sensors to identify areas where radiation over
background is detected. Characterize changes over time. Limit your response to
6 images and 500 words.
Provide your answer and
corresponding images here.
2 – Use visual analytics to represent and
analyze uncertainty in the measurement of radiation across the city.
a.
Compare
uncertainty of the static sensors to the mobile sensors. What anomalies can you
see? Are there sensors that are too uncertain to trust?
b.
Which
regions of the city have greater uncertainty of radiation measurement? Use
visual analytics to explain your rationale.
c.
What
effects do you see in the sensor readings after the earthquake and other major
events? What effect do these events have on uncertainty?
Limit your responses to 12 images and 1000 words.
Provide your answer
and corresponding images here.
3 – Given the uncertainty you
observed in question 2, are the radiation measurements reliable enough to
locate areas of concern?
a.
Highlight
potential locations of contamination, including the locations of contaminated
cars. Should St. Himark officials be worried about
contaminated cars moving around the city?
b.
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.
c.
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.
Limit your responses to 10 images and 1000 words
Provide your answer
and corresponding images here.
4 –– 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? Limit your response to 6 images and 800 words.
Provide
your answer and corresponding images here.
5 –– 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.
Provide
your answer and corresponding images here.