2015 WorkshopThe workshop for this challenge will be held October 25, 2015. For more information, see the Workshop Agenda.
About the VAST ChallengeThe Visual Analytics Science and Technology (VAST) Challenge is an annual contest with the goal of advancing the field of visual analytics through competition. The VAST Challenge is designed to help researchers understand how their software would be used in a novel analytic task and determine if their data transformations, visualizations, and interactions would be beneficial for particular analytic tasks. VAST Challenge problems provide researchers with realistic tasks and data sets for evaluating their software, as well as an opportunity to advance the field by solving more complex problems.
Researchers and software providers have repeatedly used the data sets from throughout the life of the VAST Challenge as benchmarks to demonstrate and test the capabilities of their systems. The ground truth embedded in the data sets has helped researchers evaluate and strengthen the utility of their visualizations.
Mayhem at DinoFun World
This year’s VAST Challenge presents two related mini-challenges and an overall Grand Challenge for your consideration. The challenges are open to teams and individuals in academia, industry, and government.
This year, we would like to encourage participants create innovative visualizations to support their analyses of the data. There will be many different features within the data sets that could use creative approaches, so even if your particular approach doesn’t address the entire Challenge problem set, please enter and show us your new ways of working with this data.
BackgroundNote: 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.
DinoFun World is a typical modest-sized amusement park, sitting on about 215 hectares and hosting thousands of visitors each day. It has a small town feel, but it is well known for its exciting rides and events.
One event last year was a weekend tribute to Scott Jones, internationally renowned football (“soccer,” in US terminology) star. Scott Jones is from a town nearby DinoFun World. He was a classic hometown hero, with thousands of fans who cheered his success as if he were a beloved family member. To celebrate his years of stardom in international play, DinoFun World declared “Scott Jones Weekend”, where Scott was scheduled to appear in two stage shows each on Friday, Saturday, and Sunday to talk about his life and career. In addition, a show of memorabilia related to his illustrious career would be displayed in the park’s Pavilion.
However, the event did not go as planned. Scott’s weekend was marred by crime and mayhem perpetrated by a poor, misguided and disgruntled figure from Scott’s past.
While the crimes were rapidly solved, park officials and law enforcement figures are interested in understanding just what happened during that weekend to better prepare themselves for future events. They are interested in understanding how people move and communicate in the park, as well as how patterns changes and evolve over time, and what can be understood about motivations for changing patterns.
Mini-Challenge 1Mini-Challenge 1 focuses on movement of people around the park. You are being asked to characterize the movement of groups and individuals, with a special emphasis on what might be relevant to better understanding the incident that occurred in June 2014.
Please visit VAST Challenge 2015: Mini-Challenge 1 for more information and to download the data.
Mini-Challenge 2Mini-Challenge 2 asks you to dive into the communications over time that took place among the park visitors using the park app. Linkages between visitors and among park patrons and park staff could reveal behaviors of interest.
Please visit VAST Challenge 2015: Mini-Challenge 2 for more information and to download the data.
The Grand ChallengeThe Grand Challenge requires you to blend your knowledge obtained from the two mini-challenges to answer questions of interest to law enforcement officials. How was the crime executed and who was responsible?
Please visit VAST Challenge 2015: Grand Challenge for more information.
Which Challenges Are Right for You?The two mini-challenges and the Grand Challenge are well suited to visual analytics researchers and developers with no specialized expertise required.
- Mini-Challenge 1 involves analysis of individual and group movement against a dynamic background environment.
- Mini-Challenge 2 involves analysis of communications among people over time as they act and react within the dynamic environment.
- The Grand Challenge combines what you've discovered in the mini-challenges to put together the big picture. It is ideal for individuals and teams who can blend their accumulated knowledge of activities in the mini-challenges.
Important Information about the VAST ChallengeParticipants are welcome to enter one or both of the Mini-Challenges and the Grand Challenge. Entries may be submitted by teams or individuals. Anyone not associated with the VAST Challenge Committee may submit an entry.
Submission deadlines are as follows:
- Mini-Challenge 1 and Mini-Challenge 2 submissions are due at July 7, 2015 at 11:59 pm Pacific Daylight Time (UTC/GMT -9 hours).
- For Grand Challenge submissions, an entry must be started in Precision Conference by July 7, 2015 at 11:59 pm Pacific Daylight Time (UTC/GMT -9 hours). The entry must be completed by July 9, 2015 at 11:59 pm Pacific Daylight Time (UTC/GMT -9 hours)
Instructions on how to submit your entry can be found on the VAST Challenge 2015: Submission Instructions page.
Entries will be judged based on the criteria appropriate to the specific Mini-Challenge. Award winners will receive a recognition certificate.
All participants are also invited to submit a two-page summary of their entry for inclusion in the IEEE VIS 2015 electronic conference proceedings.
All participants are invited to attend the VAST Challenge 2015 Workshop, to be held in conjunction with IEEE VIS 2015 in Chicago, Illinois. At this workshop, challenge organizers, participants, and conference attendees come together to discuss their work on this year's Challenge. Award certificates are presented during the workshop. The workshop includes presentations by participants, invited speakers, a poster session for the participants, and other activities.
Following the workshop, the submissions will be posted to the Visual Analytics Benchmark Repository. Submissions from previous years can also be found in this repository.
For questions, please email email@example.com.
1. Are the ID's unique? i.e. if we see an ID on Friday and again on Saturday, is it the same person or are they only unique in-day?
That would be the same person.
2. In MC 1.1, it asks:
''Characterize the attendance at the park on this weekend. Describe up to twelve different types of groups at the park on this weekend.
a. How big is the group type?
b. Where does this type of group like to go in the park?
c. How common is this type of group?
d. What are your other observations about this type of group?
e. What can you infer about the group?
f. If you were to make one improvement to the park to better meet this group’s needs, what would it be?''
What's the difference between (a) and (c), big and common?
For “How big is the group type?” We are just looking for a numerical answer here of how many people are typically found in the group. It may be that instead of a single number, you might want to characterize your answer as a range (e.g., “between 15-25 people”). For “How common is this type of group?” we are interested in knowing how often this kind of group shows up in the data. For example, if you see a group of 6 people who come in and then only ride slow rides (no roller coasters, because they are scary!), and then you see a different group of 6 come in and do the same thing, and then 14 other groups that do the same thing, then you have found a “type of group”. The characterization of this group could be something like this: a) this group is always 6 people in size, b) they just ride the slow rides like the train and bumper cars, and c) we found 16 different groups like this over the weekend, coming into the park at different hours of the day.
Should we only be looking at people who walk around together as “groups”?
People who move around the park together would be a group. But think about how groups behave in an amusement park. Do people who arrive at the same time always stay together the whole day? If they split apart, do they stay separate the whole day? Changes in group composition, and possible reasons for the changes, might very well be interesting.
Can one person be in different groups?
If you see situations where one person should be included in different groups, be sure to describe the differences among the groups. Also, a group that moves around the park and has particular behaviors is more interesting than just “the group of all people who ride the Log Flume ride on Saturday.” There usually isn’t anything interesting about all the riders of a particular ride all by itself. However, if everyone who visits the Log Flume on Saturday immediately leaves the park after riding it, then that is an interesting, unexpected behavior that you might want to explore. (That is just an example and is not in the dataset…)
3. Are the other attractions (shopping, etc) with no check-ins available of interest for this challenge and can it be beneficial to compute them from movements?
Even though some attractions do not have check-in data associated with them, proximity of people to attractions may very well be of interest in your investigations.
4. Does a check-in mean the visitor actually used this location (did the ride, ate at the restaurant) or is it just an information about waiting times and the visitor may decided to not do it?
It is quite possible that a person could check-in at a ride but not wait around to get to the front of the line and get on the ride.
5. When a person went to an attraction, but did not check-in, can we assume she/he did not go in?
If a person went to the vicinity of one of the rides that has check-in information available, and there was no check-in recorded, then they did not go into the ride.
6. Two rows in the Sunday Mini-Challenge 1 data appear to have format errors (lines 4332994 and 10932427).
Those two rows are in error. Please ignore them.
7. Is the Mini-Challenge 1 data missing data for Friday night after about 8 pm?
The Mini-challenge 1 data for Friday night after 8:12 pm was inadvertently omitted from the initial data release. This file contains the missing records; you can download it and add it to the data you already have.
Mini-Challenge 1 Addendum
You can download the full dataset with the missing rows included from VAST Challenge 2015: Mini-Challenge 1. Please note: if you choose to use the data originally provided, rather than the corrected data, you will not be penalized!
VAST Challenge Committee Chairs
- Kris Cook, Pacific Northwest National Laboratory
- Georges Grinstein, University of Massachusetts-Lowell
- Mark Whiting, Pacific Northwest National Laboratory