This answer sheet should be used for your VAST Challenge 2017 Mini-Challenge 1 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+2017 for more detailed instructions.    

Entry Name:  UVA-MC1

VAST Challenge 2017
Mini-Challenge 1

 

 

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

Laura Ruis, University of Amsterdam, lauraruis@live.nl

Peter van Twuyver, University of Amsterdam, pvtwuyver@gmail.com

Sven van Dam, University of Amsterdam, sven.dam@gmail.com

Student Team:  Yes

 

Tools Used:

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.

D3.js

 

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 2017 is complete? Yes

 

Video

Provide a link to your video.  Example:

http://www.westbirmingham.ac.uk/uwb-smith-mc2-video.wmv

 

 

Questions

1 – “Patterns of Life” analyses depend on recognizing repeating patterns of activities by individuals or groups. Describe up to six daily patterns of life by vehicles traveling through and within the park. Characterize the patterns by describing the kinds of vehicles participating, their spatial activities (where do they go?), their temporal activities (when does the pattern happen?), and provide a hypothesis of what the pattern represents (for example, if I drove to a coffee house every morning, but did not stay for long, you might hypothesize I’m getting coffee “to-go”). Please limit your answer to six images and 500 words.

The animated gif from Campsite8 shows the common pattern we found for the hours people arrive and leave campsites.

The graph show an example month, each Sunday in June 2015. Ranger tend to start working around 6 or 7 in the morning.

 

 

When car types 4, 5 and 6 are selected in the parallel coordinates, one can see that they never stay the night at the preserve.

Hypothesis: car types 4, 5 and 6 are public transportation.

 

When car-type 4  and number of stops 6 in the parallel coordinates visualization is selected, one can see different car ID’s that always drive the same route. These 4 axle trucks show up consistently throughout the year and always drive the same route. This is one example of a route such 4 axle truck takes, but there are more routes that get consistently travelled throughout the year by 4 axle trucks. They show up more often during high season.

Hypothesis: Professional service, like collecting waste.

 

2 – Patterns of Life analyses may also depend on understanding what patterns appear over longer periods of time (in this case, over multiple days). Describe up to six patterns of life that occur over multiple days (including across the entire data set) by vehicles traveling through and within the park. Characterize the patterns by describing the kinds of vehicles participating, their spatial activities (where do they go?), their temporal activities (when does the pattern happen?), and provide a hypothesis of what the pattern represents (for example, many vehicles showing up at the same location each Saturday at the same time may suggest some activity occurring there each Saturday). Please limit your answer to six images and 500 words.

The Linechart visualization clearly shows the seasonal pattern in the park. High season starts at 01 jun and ends at 01 october. The same chart shows the increase in traffic in the park during high season consist almost entirely of type 1, 2 and 3 vehicles. Vehicles of type 4,5,6 and 2P are steady throughout the year. The Linegraph with the traffic at the campsites shows that although there is a slight increase in Park-traffic in the low season, the campsites are nearly unused during october until may.

 

The animated visualization shows the speeding throughout the year in the park. The measure of speeding is calculated as follows:

Let n be the number of speeders on a path on one day. Let s be the average mph these speeders exceed the limit of 25 mph. The speed index is then given by:

 

n * s ^ 1.3

 

When we look at the animation, it becomes clear that there is more speeding during the summer months. This difference is mostly apparent on paths accessible by all visitors.

Paths between a gate and ranger stop show periodic patterns of speeding which remain apparent the entire year.

Paths which function as connections to get to other areas of the park show more speeding, especially the path between general gate 1 and 2. Path which for instance end in a camping and are an endpoint show less speeding.

 

 

The line above shows the busyness on the path between the ranger base and the gate in front of it. It shows that the number of visitors of the path and thus the number of rangers in the park constantly remains to be between 1 and 4 throughout the year and does not correlate with the overall busyness in the park.

The above image shows a ranger that has 49 stops and shows up throughout the year in the park, always drives the same route. This is an example of one ranger, but a lot of different reoccurring ranger paths are found during the year.

The size of the nodes above represents the number of visitors during the entire period at a type of stop (general gate and camping) relative to all other stops of the same type. It becomes clear that general gate 0 and camping 1 have very little visitors when compared to the others.

3 – Unusual patterns may be patterns of activity that changes from an established pattern, or are just difficult to explain from what you know of a situation. Describe up to six unusual patterns (either single day or multiple days) and highlight why you find them unusual. Please limit your answer to six images and 500 words.

When looking at the line chart of number of cars per day a ranger-stop1, one can see that on the 10^th of July 6 car’s or motorcycles of type 1 pass through this stop. When looking at the graph, one can see that they take an impossible route, between entrance1 and ranger-stop1.

Hypothesis: Off-road driving.

 

In the parallel coordinates a car ID with 281 check-ins stood out as an outlier. This two axle truck spent 108 days in the park and always stayed at camping 4.

Hypothesis: It looks like this car does not hand in his car ID and comes back to the park between the 19^th of June and the fifth of October.

 

When looking at the line chart of check-ins over the year in gate3, a ranger gate, one can see that a car-type 4 passes through this gate as well on a regular basis. He appears more often during high season and always during the night. He drives to ranger-stop3 and leaves the same way he came in.

Hypothesis: Some form of professional service.

 

4 –– What are the top 3 patterns you discovered that you suspect could be most impactful to bird life in the nature preserve? (Short text answer)

1.     Speeding patterns. Speeding results in louder noises and vibrations which could scare the birds away from the park and make them less inclined to lay eggs in the park.

2.     Nightly truck. The truck drives through the park at night and disturbs the peace at night very often. The truck produces noise and vibrations that are bad.

3.     Small number of visitors camping 1. A more even distribution of camping stayers among all campings would result in less busyness at the more busy campings, resulting in a more peaceful environment for the birds.