This answer
sheet should be used for your VAST Challenge 2021 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/2021/
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 2021 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
As a visual analytics expert assisting law enforcement, your
mission is to identify which GASTech employees made which purchases and
identify suspicious patterns of behavior.. You must cope with uncertainties
that result from missing, conflicting, and imperfect data to make
recommendations for further investigation.
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. Submission instructions are available here. Entry forms are
available for download below.
Questions
1 –– Using
just the credit and loyalty card data, identify the most popular locations, and
when they are popular. What anomalies do you see? What corrections would you
recommend to correct these anomalies? Please limit your answer to 8 images and
300 words.
Provide your answer and corresponding images here.
2 – Add
the vehicle data to your analysis of the credit and loyalty card data. How does
your assessment of the anomalies in question 1 change based on this new data?
What discrepancies between vehicle, credit, and loyalty card data do you find?
Please limit your answer to 8 images and 500 words.
Provide your answer and corresponding images here.
3 – Can
you infer the owners of each credit card and loyalty card? What is your
evidence? Where are there uncertainties in your method? Where are there uncertainties
in the data? Please limit your answer to 8 images and 500 words.
Provide your answer and corresponding images here.
4 –– Given the data sources provided, identify potential informal or unofficial relationships among GASTech personnel. Provide evidence for these relationships. Please limit your response to 8 images and 500 words.
Provide your answer and corresponding images here.
5 –– Do you see evidence of suspicious activity?
Identify 1- 10 locations where you believe the suspicious activity is
occurring, and why Please limit your
response to 10 images and 500 words.
Provide your answer and corresponding images here.
6 –– If you solved this mini-challenge in 2014, how
did you approach it differently this year?
Provide your answer here.