Spatial Databases - Introduction Spring, 2015 Ki-Joune Li.

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Presentation transcript:

Spatial Databases - Introduction Spring, 2015 Ki-Joune Li

STEMPNU 2 Spatial Databases What are on these images ? How to  represent,  store, and  retrieve these data

STEMPNU 3 What are on these images? These include  Pixels  Objects Buildings, Roads, Symbols, etc  Terrain Height Data  Non-Spatial Data Name of Roads, Levels of Buildings, Capacity of Bridge, etc  Relationship Between Objects Goal of Spatial Databases  Spatial databases are for representing, storing and retrieve useful information from these data

STEMPNU 4 Properties and Challenges Characteristics of Spatial Databases  Spatial Data: Very Large Amount of Data Example : more than 200 peta bytes for EOS Project  Very complicated Major Challenges  How to represent sophisticated data: Representation  How to store and manage a large amount of data: Management

STEMPNU 5 Issue I: Modeling Example  Building Spatial DB about Pusan City What is Modeling? (cf. Schema Design)  Modeling is much more important than schema design Real World Computer World

STEMPNU 6 Issue II: Management System How to Handle Large Volume of Data  Cost for Storage Media Not very important and negligible  Processing Time I/O time How to reduce disk i/o time ? DBMS Issue

STEMPNU 7 Spatial Databases ?  Databases for spatial phenomena  Spatial phenomena ? Phenomena with spatial properties Spatial properties ? What are spatial properties ?  Example Distance, Surface, Position (Coordinates) Adjacency, Connectivity

STEMPNU 8 Spatial Properties: Space Depending on the Type of Space  Euclidean Space Flat space represented by R n coordinate systems Point p is represented as an n-ary tuple (x 1,x 2, …, x n )  Road Network Space,  Terrain Space,  Indoor Space

STEMPNU 9 Open Space vs. Constraint Space Open Space  Distance is determined by the straight line connecting two points  Example: Euclidean distance (or Euclidean metric) Constrained Space  Constraint on the straight line  Distance is the length of shortest path detouring constraints  Examples of Constraint Road Network Indoor Terrain

STEMPNU 10 Example: Indoor Space Emergency Bell A 401 W.C Elevator Stairs p Real distance Emergency Bell B

STEMPNU 11 2-D space and 3-D space 3-D (cf. 2-D)  More information  Large amount of data Example  Rectangle: 4 vertices, 4 edges, and 1 face  Cube: 8 vertices, 12 edges, and 6 faces  Complicated geometric processing Example  Overlapping of two polygons  Overlapping of two polyhedrons

STEMPNU D space 2.5-D space (cf. 3-D space)  3-D space: Solid Modeling  2.5-D space Only one height value at any given point: f (x, y)=h Field and 2.5-D  Field: Terrain, Temperature distribution, etc..  2.5-dimensional representation: Field Representation

STEMPNU 13 Spatio-Temporal Model Spatial Model  Stationary objects or phenomena  Every object on the earth is moving! Spatio-Temporal Model  Object changing its location or shape according to time  Discrete change Example: Change of administrative boundary  Continuous change Example: Moving Objects, Meteorological Lines, Pollution Areas

STEMPNU 14 Topological and Geometric Properties Geometry: Geo + Metry  Geo: Earth, Space  Metry meter, metric, etc.. something to measure  Geo+Metry Something to measure in space Quantitative  m, m 2, etc.. Topology  Relationship between Spatial Objects  Qualitative adjacent, inside, left, right

STEMPNU 15 Spatial Database Building Procedure Comparison with Software Life Cycle Comparison with Building Construction

STEMPNU 16 Spatial Database Building Procedure Requirement Analysis  Scope of databases: depends on applications  Data Items, Attributes, Accuracy, etc..  Use-Case Diagram Current State: As it isAs it must be

STEMPNU 17 Spatial Database Building Procedure Data Modeling  Understanding the real world and application  A very small piece of the real world According to viewpoint Determined by applications  Drawing what you have understood in formal method Example. UML 4 steps  Requirement Analysis  Entity and Granularity  Attributes  Relationships

STEMPNU 18 Spatial Database Building Procedure Data Collection  Legacy System and Databases  Interoperability and Standard Issue  Data Generalization  Metadata Data Input  Relies on Manual work  Automatization

STEMPNU 19 Spatial Database Building Procedure Quality Control  Check the correctness of data Maintenance  Periodic Backup  Updates Equivalent to 30% of the total amount of data Determine the quality of DB