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The 2012 Visual Analytics Science and Technology (VAST) Challenge posed two challenge problems for participants to solve using a combination of visual analytics software and their own analytic reasoning abilities. Challenge 1 (C1) involved visualizing the network health of the fictitious Bank of Money to provide situation awareness and identify emerging trends that could signify network issues. Challenge 2 (C2) involved identifying the issues of concern within a region of the Bank of Money network experiencing operational difficulties utilizing the provided network logs. Participants were asked to analyze the data and provide solutions and explanations for both challenges. The data sets were downloaded by nearly 1100 people by the close of submissions. The VAST Challenge received 40 submissions with participants from 12 different countries, and 14 awards were given.

Global Positioning System technology has the potential to revolutionize both commercial and military aircraft landing procedures. It will enable pilots to fly complex, curved approaches rather than the more simple straight-in approaches necessitated by the Instrument Landing System used at most large airports. To complement this technology, Head-Up Display pathway symbology was developed for use in the aircraft to help pilots stay on course during these complex landings. Thirteen Air Force pilots used this pathway symbology in a simulator to land under Visual Meteorological, Partial Instrument Meteorological and Full Instrument Meteorological visibility conditions. Deviations from commanded flight path, as well as lateral and longitudinal deviations from a desired runway touchdown point, were measured. Results indicated that landing performance was acceptable for all pilots and functionally equivalent in all weather conditions. Results of this study suggest that pathway symbology could provide the cues necessary to successfully fly complex, curved approaches to landing. In addition, the merits of using Equivalency Analysis, rather than traditional Analysis of Variance in testing for performance differences is discussed.

A fictitious amusement park and a larger-than-life hometown football hero provided participants in the VAST Challenge 2015 with an engaging yet complex storyline and setting in which to analyze movement and communication patterns. The datasets for the 2015 challenge were large-averaging nearly 10 million records per day over a three day period-with a simple straightforward structured format. The simplicity of the format belied a complex wealth of features contained in the data that needed to be discovered and understood to solve the tasks and questions that were posed. Two Mini-Challenges and a Grand Challenge compose the 2015 competition. Mini-Challenge 1 contained structured location and date-time data for park visitors, against which participants were to discern groups and their activities. Mini-Challenge 2 contained structured communication data consisting of metadata about time-stamped text messages sent between park visitors. The Grand Challenge required participants to use both movement and communication data to hypothesize when a crime was committed and identify the most likely suspects from all the park visitors. The VAST Challenge 2015 received 74 submissions, and the datasets were downloaded, at least partially, from 26 countries.