Entry Name: UBA-Cesario_Lamagna_Picoaga-MC2
VAST
Challenge 2014
Mini-Challenge 2
Team Members:
Diego Martin Cesario, University of Buenos Aires (UBA), diegomcesario@gmail.com PRIMARY
Walter Lamagna, University of Buenos Aires (UBA), wlamagna@gmail.com (Point of contact for
questions/answers)
Jorge Kuday Picoaga, University of Buenos Aires (UBA), georgepicoaga@gmail.com (Point of
contact for questions/answers)
Student Team: YES
Analytic Tools Used:
Tableau
GTM, Geotemporal Multivariate developed in html5 and Processing language programing by Walter Lamagna.
Mapinfo, Mapbasic (programing module)
MapsearchVast, developed in Mapbasic developed in Mapbasic by Jorge Picoaga, and adapted for the challenge.
Oracle 12c database (Sql Spatial query advanced)
Approximately how many hours were spent
working on this submission in total?
360
May we post your submission in the
Visual Analytics Benchmark Repository after VAST Challenge 2014 is complete? YES
Video:
http://www.wallves.com/vast/MC2_Team38.wmv
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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.
a) In what hours they work.
Each day, typical GASTech employee leave home and go to work around 7:00 am
(Fig.1), arriving to GASTech between 8 and 8:30h. Typical shift is from 9 to 5.
Many of them live near to the coast and therefore must travel the entire city
to reach Gastech allocated in south of the city, however, all the staff members
usually arrive at work on time. (Fig.2).
Image 1/5 - SQL query between 6am and 7am in the morning + Geographical
Thematic grouped by ID map was useful technic to get the daily GASTech
employees departures.
Image 2/5 - With Thematic Maps we can see all the GASTech afluency to the
company around the 9am.
b) Usual activities before arrive to work. As common individual GASTech
employees take a Breakfast in a way to work. Brew Awakenings and Hallowed
Grounds are visited for Executives and Bean there done That for the rest of the
GASTech staff. (Fig.4)
Image 3/5 - Making clusters by Employee area inside the track data we can
obtain the preference places to Executives breakfast time.
c) When often they have a break. Around the noon they have their snack time.
Executives and Engineers prefer lunch at Guy's Gyros, Ouzeri Elian, Katerina
Cafe while security staff on the other hand prefer go to Kalami Kafenion, Guy's
Gyros, Ouzeri Elian and the technology people go to Hippokampos, Guy's Gyros,
Gelatogalore . (Fig.3) There are not register from Truckers lunch time or
place.
Image 4/5 - This image comes from a custom visualization on the GTM Tool. It
consists of two columns , one per week. And each column has 45 columns,
representing each a person. The colored bars are places, and each color is a
place. The red color shows when they are in GASTech, consistent with the time
period described. During the lunch each person and work group has a preference
for a place. The tool has an integrated timeline, one can choose a person and
it shows everybody that purchased in that place at that time.
d) Weekend activities: Includes no common patterns, usually they register
movement on the coast side around the noon. All the top executives plays golf
the Sundays (Fig.4). Truckers cannot be tracked weekend because their assigned
vehicles are left in the company during the weekends. e) Usual activities after
work. Gastech employees are accustomed to dining out in their places preferably
between 8 and 9 pm. Hippokampos is visited commonly for Executives at this
time, the rest of the staff have not preference places to dinner.(Fig 5).
Image 5/5 - Executives weekend activities include playing Golf at Sundays noon.
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?
Please limit your answer to no more than twelve images and 1500 words.
1) Long away meeting activity during
working hours Suspect meeting between different areas staff members take place
in Gelatogalore. Location involved in this issue is Ithankis / Alexandrias
intersection streets, this place is not near from GASTech and was visited
between business hours. Employees involved in the issue includes Campo-Corrente
Ada, Alcazar Lucas, Bergen Linnea, Osvaldo Hennie, Onda Marin, Vasco-Pais
Willem What locations are involved? Gelatogalore (Ithankis / Alexandrias) When
does the pattern or event take place? 01/07/2014 13:20 Why is this pattern or
event significant? This meeting is consider as suspect because the break place
chosen for the employees does not include far away locations. Thus, long travel
between offices hours need to be justifying with important issue.
What is your level of confidence about this pattern or event? Why? 100% GPS
data was investigate in order to get evidence.
2) Modified and / or adulterated Data The time (transaction time) were modified
in the credit card records of 4 places, This strange patterns involves to Lars
Azada, Felix Balas, Axel Calzas, Gustav Cazar, Lidelse Dedos, Birgitta Frente,
Vira Frente, Ingrid Barranco, Loreto Bodogri, Islande Borrasca, Ada
Campo-Corrente, Varro Awelon, Isak Baza, Elsa Orilla, Orhan Strum, Willem
Vasco-Pais Modified data in Timestamp data was get in Brewed Awakenings, Bean
There Done That, Coffee Shack and Jack's Magical Beans between 6th and 17tn in
January Why is this pattern or event significant? We assume this data was
modified to hide when meetings take place and employees involved in the issue.
What is your level of confidence about this pattern or event? Why? 100%, when
this data was fixed matching tracks with credit card transaction we were
allowed to find the meeting in the locations.
3) Vehicles with more than one person Some truckers driving with other / others
GASTech employees in their daily routes. Hafon Albina (with Hawelon Claudio and
Hawelon Benito), Scozzese Dylan (with Adan Morlum), Nant Irene (with Cecilia
Morluniau) are involved in this issue.
What locations are involved?
Abila Aiport, National Refinery, Maximum Iron and Steel, Abila Scrayard,
Carlyle Chemical Inc., Stewart and Sons Fabrication
The event takes place in all daily truckers routes. This event is significant
because each trucker must cover his/her daily route assigned and he / she is
responsible for unique vehicule. Confidence Level: 100% Credit Card and GPS
data were matched successfully in order to allocated the lack of 4 truckers in
all the period of time.
4) Cuted tracks
It was checked cut tracks for 2 GASTech employees. Alex Caldas and Irene Nant
are involved in the issue Axel Calzas Track is detected cutted the January 10th
between Carden and Fillis streest intersection at 7:59h and is visualized again
at 8:10h in the Utmana and Aveny street interseccion. The same day is detected
other cut in Brada / Hacia street interseccion at 17:39h and track can be see
again at 19:11h in Limnou / Darloniau street intersecction. On the other hand.
Irene Nant track is detected cutted N. Mattadou St / N. Alamanas St
intersection (Carlyle Chemical) at 01/15/2014 18:25:24, next day Truck
departure is from GASTech. Investigation must cover all the employees tracks in
order to analyze rare issues. GIS can represent this data with time details therefore
our confidence level is 100%
5) Employee departure from another address
What is the pattern or event you observe? 2 Employees departure is from another
co-worker address.
Ada Campo Corrente, Loreto Bodogri, Willem Vasco-Pais, Issia Vann are involved
on the issue. What locations are involved? Ada Campo-Corrente (Blant / Nia
intersection) and Willem Vasco-Pais (Utmana / Billar intersection) addresses.
When does the pattern or event take place? 11/1 Issia Vann go to the Willem
Vasco-Pais at 3:30am, 7/1 Loreto Bodogri go to the Ada Campo-Corrente at
3:20am. Why is this pattern or event significant? This event is evidence of a
suspect kind of relation between Executive employees and co-workers.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
6) Visit to the Chostus Hotel
Some GASTech employees visit and make a transaction on Chostus Hotel. The
employees identify involved in this issue are: Dedos Lidelse, Frente Birgitta,
Tempestad Brand, Borrasca Isande.
What locations are involved? Chostus Hotel in several days that include Jan
7/10/14/17 Why is this pattern or event significant? This activity in working days
is a suspect activity / behavior for our investigation.
What is your level of confidence about this pattern or event? Why?
100% Tracks in the MapTool and Credit Card transaction were matched to reach
this evidence.
7) GASTech activity in non-working hours
IT employee Lucas Alcazar track data shows activity out of business hours. The
location involved is GASTech and strange pattern was identify at 01/07/2014
around the 01:10:01 Due to employees schedules was not provided this issue is
consider as Suspect activity.
Level of confidence: 100% This data was collect from GPS Track of this employee
8) Suspect meeting place on Saturday 18th
Suspect meeting between some GASTech employees. The employees involved
includes:
Orhan Strum, Lucas Alzazar, Vara Lagos, Ada Campo-Corrente, Isande Borrasca,
Loreto Bodrogi.
What locations are involved?
Intersection between Skarkeme / Arkadiou streets, named Suspect place 10 in our
suspect places own table. The meeting take place the 01/18/2014 at 13:36:42 Why
is this pattern or event significant? Day and location of this meeting is
considered as suspect for its location.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
9) Suspect meeting place on January 15th
Suspect meeting between some GASTech employees. The employees involved includes:
Hennie Osvaldo, Loreto Bodrogi, Inga Ferro, Minke Mies.
What locations are involved?
Intersection between Agentes/ Maskin streets, named Suspect place 8 in our
suspect places own table. The meeting take place the "01/15/2014 12:10:01
and we have register of other visites to same place the 6/8/9/13/14/17.
Why is this pattern or event significant?
Location of this meeting is considered as suspect for its location.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
10) Suspect meeting place on January 11th
Suspect meeting between some GASTech employees. The employees involved include:
Hennie Osvaldo, Loreto Bodrogi, Inga Ferro, Minke Mies, Isia Vann, Edvard Vann.
What locations are involved?
Intersection between Exadakitiou Way/ Matadou streets, named Suspect place 6 in
our suspect places own table. The meeting take place the 01/11/2014 03:25:54
Why is this pattern or event significant?
Location of this meeting is considered as suspect for its location.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
11) Suspect visit to suspect place on January 7/8/13/15.
Suspect visits to suspect place identified. The employees involved include:
Hennie Osvaldo, Loreto Bodrogi, Inga Ferro, Minke Mies
What locations are involved?
Intersection between Evripidou/ Eleftherias streets, named Suspect place 7 in
our suspect places own table. The meeting takes place several days around
11:30:00.
Why is this pattern or event significant?
Location of this meeting is considered as suspect by its location.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
12) Suspect visit to suspect place on January 7/9/10/11/14/16
Suspect visits to suspect place identified. The employees involved include:
Hennie Osvaldo, Loreto Bodrogi, Inga Ferro, Minke Mies, Inga Ferro
What locations are involved?
Intersection between Gerantoni / Aveny streets, named Suspect place 2 in our
suspect places own table. The meeting take place several days around 11:30:01
several days.
Why is this pattern or event significant?
Location of this meeting is considered as suspect by its location.
What is your level of confidence about this pattern or event? Why?
100% GPS data was investigate in order to get evidence.
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.
a) Conflicting data/Outliers : Employee
28 track (Elsa Orilla) : The data for this employee , a technical error in the
GPS signal is thus separated from the rest of the data to facilitate our
research and considered as outlier
Fig1. Track outlier Elsa Orilla was isolated before start our investigation.
b) Missing data: Credit card data: Some transactions have the wrong day.
Therefore it is considered as conflicting data.
Fig2. Four places were detected with missing timestamp data and It was needed
cover with the correct data.
c) Missing data: Lack of data in the table Street: This table is incomplete,
some important considerations when finding homes and places fields had to be
mathematically calculated to meet our goal.
Fig3. Near to 380 addresses rows was incompleted and Geographical method was
used in order to cover this lack of information (Data completed was needed to
reach the Employees addresses)
d) Data of varying resolutions: Different scale raster image: Tourist map
raster image (useful initially to allocate the first reference about the
important places), was provided with different geographic scales for our GIS
tool. It had to be fixed by a cross mathematically coordinate with the table of
streets in order to get correct geographic scale.
Fig4. Tourist map jpg image was provided with different scale than Abila street
data. It was needed create a coordinate reference in order to get the first
places allocation.
e) Missing data: Lack of tables with Consuming locations and Employees
Addresses involved in the research: This data was not provided therefore it was
needed to be created
Fig5. Due to tables with Important Places and GASTech employees addresses
coordinates were not provided, some advanced spatial queries were GIS technics
to create street intersection and overlapping spatial objects new tables.