VAST Challenge 2014: Mini-Challenge 2



IEEE VAST Challenge 2014 is open for submissions! The VAST Challenge uses the Precision Conference System (PCS) to handle the submission and reviewing process. PCS is available at https://precisionconference.com/~vgtc/. If you do not already have a login for the system you must register first. Once you are logged into your account please choose VAST 2014 Challenge under “new submissions” and follow the instructions.

Frequently-asked questions will be added at the bottom of this page as they are received. Check back frequently for updated information.

April 30, 2014 - The KML file distributed with Mini-Challenge 2 has been updated to better reflect street names. This is not expected to affect your solutions to Mini-Challenge 2 but may be helpful to participants in Mini-Challenge 3 and the Grand Challenge. You can obtain the updated data by downloading the dataset and associated information below. The only file that has changed is Abila.kml.


Note: This scenario and all the people, places, groups, technologies, contained therein are fictitious. Any resemblance to real people, places, groups, or technologies is purely coincidental.

Many of the Abila, Kronos-based employees of GAStech have company cars which are approved for both personal and business use. Those who do not have company cars have the ability to check out company trucks for business use, but these trucks cannot be used for personal business.

Employees with company cars are happy to have these vehicles, because the company cars are generally much higher quality than the cars they would be able to afford otherwise. However, GAStech does not trust their employees. Without the employees’ knowledge, GAStech has installed geospatial tracking software in the company vehicles. The vehicles are tracked periodically as long as they are moving.

This vehicle tracking data has been made available to law enforcement to support their investigation. Unfortunately, data is not available for the day the GAStech employees went missing. Data is only available for the two weeks prior to the disappearance.

In addition to the vehicle data, law enforcement has been given access to the personal and business credit and debit card transactions for the local GAStech employees for the two weeks preceding the kidnapping. Many of the GAStech employees also use loyalty cards to gain discounts or extra benefits at the businesses they patronize, and law enforcement has been given access to two weeks of this loyalty card data as well.

As a visual analytics expert assisting law enforcement, your mission is to make sense of this data to identify suspicious patterns of behavior and to prioritize which of these may be related to the missing staff members. 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 for Participants

MC2.1 – Describe 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.

MC2.2 – Identify 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
  1. What is the pattern or event you observe?
  2. Who is involved?
  3. What locations are involved?
  4. When does the pattern or event take place?
  5. Why is this pattern or event significant?
  6. 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.

MC2.3 – Like 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.

Available Data

As an analyst, you have a set of materials at your disposal:

  • A list of vehicle assignments by employee, in CSV format (car-assignments.csv)
    • Employee Last Name
    • Employee First Name
    • Car ID (integer)
    • Current Employment Type (Department; categorical)
    • Current Employment Title (job title; categorical)
  • ESRI shapefiles of Abila and Kronos (in the Geospatial folder)
  • A CSV file of vehicle tracking data (gps.csv)
    • Timestamp
    • Car ID (integer)
    • Latitude
    • Longitude
  • A CSV file containing loyalty card transaction data (loyalty_data.csv)
    • Timestamp
    • Location (name of the business)
    • Price (real)
    • FirstName (first name of the card holder)
    • LastName (last name of the card holder)
  • A CSV file containing credit and debit card transaction data (cc_data.csv)
    • Timestamp
    • Location (name of the business)
    • Price (real)
    • FirstName (first name of the card holder)
    • LastName (last name of the card holder)
  • A tourist map of Abila with locations of interest identified, in JPEG format (MC2-Tourist.jpg)

Download the Datasets, Entry Forms, and Documentation

Enter your email address below to download the datasets, entry forms, and documentation. The links to download the data will appear below.

Frequently Asked Questions

Question 1: Can you provide additional information about the rewards associated with loyalty cards? Can loyalty cards be linked together? Are ID numbers available for the loyalty cards?

Answer: Only very limited information is available for the loyalty cards. No information is available about specific rewards associated with the cards. ID numbers are not available for the cards.

Question 2: Do the GPS satellites used in conjunction with the gps.csv have a sensor model(s) attached?

Answer: The law enforcement agency on Kronos that obtained the GPS logs from GAStech did not provide any additional information on the GPS logging equipment or the satellite system. The log locations should be taken at face value.

Page last modified on Monday, June 23, 2014