This Answer Sheet should be used for your VAST Challenge 2014 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 http://vacommunity.org/VAST+Challenge+2014 for more detailed instructions.    

Entry Name:  "UWB-Smith-MC2"

VAST Challenge 2014
Mini-Challenge 2

 

 

Team Members:

Replace this list of team members with the names, affiliations, and email addresses of your own team. Indicate the primary point of contact.  Example:

Marion Smith, University of West Birmingham, smith@westbirmingham.ac.uk     PRIMARY
Paul White, University of Northeastern Washington, white@unew.edu


Student Team:  Please enter a YES or NO

 

Analytic Tools Used:

Provide a list of analytic 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 2014 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

 

 

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Questions

 

MC2.1Describe common daily routines for GAStech employees. What does a day in the life of a typical GAStech employee look like?  Please limit your response to no more than five images and 300 words.

 

Provide your answer and corresponding images here.

 

MC2.2Identify up to twelve unusual events or patterns that you see in the data. If you identify more than twelve patterns during your analysis, focus your answer on the patterns you consider to be most important for further investigation to help find the missing staff members. For each pattern or event you identify, describe

a.       What is the pattern or event you observe?

b.      Who is involved?

c.       What locations are involved?

d.      When does the pattern or event take place?

e.      Why is this pattern or event significant?

f.        What is your level of confidence about this pattern or event?  Why?

 

Please limit your answer to no more than twelve images and 1500 words.

 

 

Provide your answer and corresponding images here.

 

 

MC2.3Like most datasets, the data you were provided is imperfect, with possible issues such as missing data, conflicting data, data of varying resolutions, outliers, or other kinds of confusing data.  Considering MC2 data is primarily spatiotemporal, describe how you identified and addressed the uncertainties and conflicts inherent in this data to reach your conclusions in questions MC2.1 and MC2.2.  Please limit your response to no more than five images and 300 words.

 

 

Provide your answer and corresponding images here.