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Modeling Storing and Mining Moving Object Databases

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Modeling Storing and Mining Moving Object Databases. Proceedings of the ... The figure below shows a spatiotemporal space (the cube in solid lines) and ... – PowerPoint PPT presentation

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Title: Modeling Storing and Mining Moving Object Databases


1
Modeling Storing and Mining Moving Object
Databases
  • Proceedings of the International Database
    Engineering and Applications Symposium (IDEAS04)
  • Sotiris Brakatsoulas
  • Dieter Pfoser
  • Nectaria Tryfona
  • Presentation by
  • Michael J. Dudley

2
What is a Moving Object Database?
  • A Moving Object Database (MOD) consists of
  • Spatial Data
  • Infrastructure information
  • Roads, Buildings, Obstructions, etc
  • Non-spatial Data
  • Other thematic information
  • Trajectories
  • New area of research

3
Spacial and Non-spacial Data
  • Both scenarios are well explored research topics
  • Many DBMS allow for their manipulation.

4
Trajectories
  • New field of research
  • No commercial DBMS are available to manage the
    trajectory data

5
Handling Trajectories
  • Pre-process the data
  • Deal with errors in positional measurements
  • Data Modeling
  • Define a conceptual model to meet systems
    requirements
  • Data Storage
  • Logical data models, data types and query
    processing issues

6
What is a MOD use for?
  • Registering current information is not enough
  • A MOD must be able to extract further knowledge
    about a system
  • Mini-World Fortune Teller

7
????????S System
  • ????????S means Path Finder in Greek
  • I will use the English translation when
    discussing this system
  • The Path Finder System(PFS) of Athens, Greece
  • Focuses on extracting further information about
    the movement of vehicles in the Athens municipal
    area.
  • Additional information about traffic conditions
  • Optimal routes
  • Prediction of troublesome situations

8
PFS History
  • PFS is a research project focusing on the
    development of a traffic management system
  • Two main goals
  • Registration of the semantics of moving object
    data in an object-oriented way resulting in a MOD
  • Adaptation of well known and widely used mining
    functions of characterization, clustering, and
    association in the moving object application
    domain and their expression through SML, allowing
    for a formal application in MOD

9
PFS Core Components
  • The Charateriser
  • Cluster Finder
  • Associator
  • All three are used to perform data extraction on
    the MOD

10
Article vs. Presentation
  • Article
  • Section 2 Organization of the database
  • Section 3 Pre-processing, modeling and storage
    issues related to trajectory data
  • Section 4 Architecture and components of the
    PFS
  • Section 5 Analyses the mining process and
    presents the spatial mining language
  • Presentation
  • I will focus on Section 2 for the remainder of
    this presentation
  • Please contact me if you would like a full copy
    of this article.

11
Organizing the MOD
  • It is essential to study
  • the movement of objects
  • their properties and relations
  • Fundamental concept of movements of objects
  • After defining the semantics we organize them
    into a database, the MOD

12
The semantics of movement
  • Represent a moving object as point object
  • Volume and size do not play a critical role
  • This point object can be represented in a 3D
    graph
  • Space (x, y)
  • Time (t)

13
The semantics of movement
  • Need the moving objects position on a continual
    basic
  • Current GPS and telecommunications technologies
    obtain position at discrete instances of time
  • By interpolating these samples we can extract the
    movement of the object
  • Linear interpolating takes the sample positions
    and makes them the ends points of line segments.
    The combination of the line segments makes an
    line in three-dimensional space

14
The semantics of movement
The solid line below represents the movement of a
point object. Space (x- and y-axes) and time
(t-axis) are combined to form a 3D-area.
Modeling Storing and Mining Moving Object
Databases pg 3.
15
The semantics of movement
The figure below shows a spatiotemporal space
(the cube in solid lines) and several
trajectories (the solid lines) contained in it.
Time moves in the upward direction, and the top
of the cube is the time of the most recent
position. The wavy-dotted lines on top symbolize
the growth of the cube with time.
Modeling Storing and Mining Moving Object
Databases pg 3.
16
The semantics of movement
  • In this study, the previous trajectory
    representation in three-dimensional space was
    chosen to be adequate to derive the properties
    and relationships of the object movement.
  • Answers both simple and complex questions
  • Which area did a vehicle cover during its trip?
  • Which vehicles left Athens after midnight moving
    East and were found close to each other 2 hours
    later?

17
The semantics of movement
  • Properties based on requirements
  • The speed of the movement
  • The heading
  • The direction of the vehicle
  • The covered area
  • Indicating the area the vehicle covered during
    its trip
  • The traveled distance
  • The traveled time

18
The semantics of movement
  • Relationships
  • Relations between a trajectory and its spatial
    environment
  • Relations among trajectories

19
The semantics of movement
  • Relations between a trajectory and its spatial
    environment (trajectory/spatial)
  • Infrastructure elements
  • Roads, Buildings, Parks, etc
  • Imaginary entities
  • City boundaries or query regions
  • In a temporal context these spatial entities
    become three-dimensional represented by a 3D
    region

20
The semantics of movement
  • Five basic spatial relationships
  • Stay Within
  • Bypass
  • Leave
  • Enter
  • Cross

Modeling Storing and Mining Moving Object
Databases pg 3.
21
The semantics of movement
  • Relations among trajectories (trajectory/trajector
    y)
  • Additional relevant to spatial relationship
  • Based on topological reasoning

22
The semantics of movement
  • Five common relations among trajectories
  • Intersect
  • Meet
  • Equal
  • Near
  • Far

Modeling Storing and Mining Moving Object
Databases pg 3.
23
The Database Schema of MOD
  • Previous concepts needs to be organized to define
    the data model of MOD
  • Use the class diagram of UML for the conceptual
    representation due to its popularity and high
    degree of comprehension and expressiveness.

24
The Database Schema of MOD
Modeling Storing and Mining Moving Object
Databases pg 4.
25
The Database Schema of MOD
  • Trajectory Class
  • To capture a trajectory
  • Trajectory ID
  • Vehicle ID
  • Position
  • Set of Operations
  • GetPosition
  • GetSpeed
  • GetTime
  • TravelledDistance
  • GetHeading

Modeling Storing and Mining Moving Object
Databases pg 4.
26
The Database Schema of MOD
  • 3D-region Class
  • Denotes the spatial environment of the trajectory
  • In this case it shows total covered area

Modeling Storing and Mining Moving Object
Databases pg 4.
27
The Database Schema of MOD
  • Trajectories have one or more relations with
    other trajectories or their 3D-region class.

Modeling Storing and Mining Moving Object
Databases pg 4.
28
The Database Schema of MOD
  • This style of representation has the advantage of
    describing two basic concepts
  • The trajectory of the moving object by keeping
    track of its movement
  • The moving object by recording its last known
    position

29
Questions
  • The road network of Athens, Greece

Modeling Storing and Mining Moving Object
Databases pg 5.
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