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Entry Name: "UWB-Smith-MC2"

VAST Challenge 2014
Mini-Challenge 2

Team Members:

Fernando Croceri fernando.croceri@gmail.com Universidad de Buenos Aires

Pablo Guzzi guzzipa@gmail.com Uiversidad de Buenos Aires

Student Team: Yes

Analytic Tools Used:

Tableau 8.1

QGis

Excel 2010

SAS Enterprise Guide

Approximately how many hours were spent working on this submission in total?

30 hs

May we post your submission in the Visual Analytics Benchmark Repository after VAST Challenge 2014 is complete?

Yes

Video:

http://youtu.be/oB0XPfkEKz0

VAST2

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Questions

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.

Tracking GASTech Employees Routes

The first three images (Figure 1) represent a GASTech employee typical day, in relation to their patterns of movements over 13 days. These are represented by five ranges of red.

The routine of these employees show that the city center, in terms of movements concentration, is GAStech. Furthermore it can be seen that another travelled route is the one that leads to the airport zone and the route to the port of Abila specially Ipsilantou Avenue. Finally, the two images below the big map represent the same routes but with larger grid trimmings. This is very useful to focus on the most traffic areas.

In order to continue with the analysis the figure 2 is shown below. This figure was called the “heat-maps infography” because it represents a good way to see how Abila´s people moves around different days and hours. In the first graph we can clearly see how the cars move more frequently around early hours in the morning, at the lunch hour and at the closing time. Although it can also be seen that some days at 3 : 00 am there is an unusual movement. In this context and to enter into details, we made two more heat-maps, one by hour, and the other by day. At figure 2.2 (by hour) it can be seen that there are movements at dawning especially around 3 AM. Finally, the image 2.4 shows the distributions of variable day and hour, bringing a global vision of Abila´s people movements. In this way, day 16 is the most active day and this was tracked between 5 pm and 8 pm. The same applies for day 10 (Friday) between 9PM and 12AM.

Tracking GASTech Employees Purchases

The four tree-maps below show the diverse patterns of purchases in the different moments of day (Dawning, Morning, Lunch Time and Night). At the beginning

of the image, there is a bar graph with the total of purchases, to take into count the scale. Each tree-map has its own scale to make the comparison at the different times of the day possible.

Those businesses that show more sales in the morning don´t show a lot of sales in the lunch time or at night. The same thing occurs with lunch time in relation to the night.

The shops that have big sells in the morning are Brew’ve Been Served, Hallowed Grounds and Coffee Cameleon.

At the noon or afternoon, the business where GASTech employees purchase more are Hippokampos, Gelatogalore,Katerina´s Café, Abila Zacharo,

Been There Done That, Ouzeri Elian, Guy´s Gyros and other´s more. In the night, the ranking starts with Katerina´s Café, Hallowed Grounds, Hippokampos and Frydos Autosupply.

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

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?

Strange Movements at Dawning

So as to continue with MC2.2, the figure 4 contains 4 images with patterns of movements in strange moments of day. This pattern illustrates that some of the GASTech employees take the place of other person generally around 3: 30 am between Sperson Park , Taxiarchon Park and Spetson Street. Also, there is a strange movement in GASTech company on January 7^th, but it seems to us that it could have been a large working day that finished at 1 am. The level of confidence for this events is high, because these movements are repeated by same people at the same hour to the same place.

Purchases and Purchases

The title of this visualization refers to the fact that with the following images below you can see all purchases by different types of employment in GASTech by day and hour, the distribution by location and other facts.

The first graph contains all purchases, where the size of the bubbles represents the amount of purchases and the colour of the bubble represents the value of the purchases.

There are a lot of strange purchases like:

ü President (CEO) Purchases: He only bought on the Friday, Saturday and Sunday prior to the kidnapping.

ü Highest Values Purchases are made by trucks drivers in average.

ü There are some purchases at 3 am, there are not big but very strange.

The Figure 5.2 shows the same data but each row is divided by the total of the row. By this way the image shows in a better way the strange movements for the different jobs.

The red point shows that some types of employees spent a lot in some days at some hours like de It Helpdesk, the Ceo and the Site control.

These visualizations are significant because it’s important to analyze the patterns of purchases that different employees of GASTech make. The suspicious hours, high amounts of purchases or value may be indicating an unusual event.

The figure 5.3 shows the purchases distribution in box plot by Location. The most expensive purchases are made in Abila Airport, Calyle Chemical Inc., Maximum Iron and steel and Stewart and Sons Fabrication.

But the most relevant aspect in the graph is an outlier: Lucas Alcazar makes a purchase for US$ 10.000 in Frydos Autosupply n'More when the purchases at this location are much smaller on average and also have very low variability. In connection with the figures 5.1 and 5.2 we can see that, because Lucas Alcazar is IT HelpDesk, the bubble in red in that row represents his purchase at 13^th at 7 pm approximately.

GASTech Employees Houses : Who starts a new day out of his house?

The Figure 6 refers to the first movement of the day (after 5am, in order to prevent bias with the movements in the Dawning).

The most of employees start at the same place in the morning, but at some different starting point depending on the day. For example, Axel Calzas starts the day in 5 different places, each with different frequency.

The same occurs with Adra Nubarron, she lives near Guy's Gyros but some day she starts the day in Kronos Capital. This behavior is repeated for Hennie Osvaldo, he awakens one day in the Birgitta Frente's house, but for the majority of days we can say that his house is near of Frydos Autosupply.

Speed UP!

In the next figure, you can see how some of the GASTech employees start to make longer distances and increase the average of speed along the different days. Although the colour is not so useful to discrimine betewen 13 days, the point that moves away from the cloud increases the speed average and the total distance traveled. This guys are Mies Henk, Scozzese Dylan, Hawelon Benito, Hafon albina and Cecilia Morliniua.

To make the previous image more complete, this BOX-PLOT shows a very similar thing but in a different way. In general Mies Henk has his speed average above the others employees.

Also, there is another outlier that is the President of GASTech that the 19^th of January increases the average transfer speed.

Strange Movements = Truck Drivers ?

In the figures below, you can see the unusual activities of truck drivers after 5 pm some days. The size of the images attempt to represent the activity of the day.

In the first images, the smallest ones, you can see that there is no activity for truck drivers, excepting for the manager of facilities ( Truck Drivers Boss). But at 13^th, 15^th, and specially 16^th the truck drivers increment a lot the trips along the city past 5 pm. These patterns seem to be important to us because some truck drivers repeated the circuit, but it is very strange that they show activity near a nonworking hour. To complement this figure, you can see at the end a bar graph with the distribution by day.

Going for Dinner? Or for a Strange Meeting at Abila?

The images below show with a heatmap the traffic of the day when the meeting at the House of Lars Azada occurred, January 10th. The Departure to Lars house, was betewen 5 pm to 8 pm. The return to eachone houses was past 8 pm.The biggest map illustrates the total traffic to the meeting and the two images below explain the departure and the returning of the meeting.

This event seems very important to us because a lot of GASTech employees go to the meeting. Although it could be a social meeting, like having an “engineer dinner”, this event might not be a simple meeting of friends.

Another thing to mentionate is that at the middle of the meeting Lars Azada went out of the house to Hippocampos and make some purchases with credit card and then Lars come back to the meeting.

Before the disappearance, two meetings in two different points

The Figure 11, shows like figure 10 a heatmap with to meetings at 19^th of January, the day before the disappearance of some GASTech Employees. It´s a very simple image that shows how the different GASTech Employees goes to two dissimilar poinst at the city and make purchases on the shops at those blocks. The 19^th is Sunday, and the hour of the event is past 5pm, so it seems to us to be a very unusual and suspicious movements. To complement the map, the image below contains the similar image with the purchases at that time by those people. You can find diverse credit card purchases 30 minutes at that place.

So as to make us speculate if that is a just an accident, or there was something synchronized concerning the 11 citizens involved in  that circumstance.

The confidence of this event is very high because is one day after the disappeareance

To bussy to come back to the office?

The Figure 12 shows how the ID Car 1, Alcazar Lucas make atypical movements during non-working hours(9PM to  4AM). Moreover, these movements are round trip between his home and GASTech despite being outside of typical working hours. The person has 4 round trips in the nigth the days 6th, 8th, 15th and 17th. All of them are made of around 12 at night.

Below you can see the distribution of mobility Alcazar. In gray are considered more normal times and in blue, hours when activity related to the company can be symbol of suspicion.

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.

The GPS points determined by the ID 28 had a marked dispersion regarding the remaining points. But the frequency points are normal in reference to the rest of the GPS. To solve this we apply a no parametric regression (LOESS Regression) characterized by the computational cost involved, this regression was originally developed as a method of visualization. 

This is characterized by smoothing parameter which determines the linearity of the final result. The regression was applied to the Latitude and Longitude separately with the following results.

In the car assignments table there wasn’t information about who was driving the trucks. Apparently the different trucks are assigned to driver with rotative days.

Therefore we use the GPS data for associate the ID Car with each Driver Truck.