Transcript Spatial Database : Introduction

Spatial databases:
Introduction
Geog 495: GIS database design
Outlines
• Decoding the acronym GIS
• GIScience view on spatial database
• DBMS view on spatial database
• Review questions
1. Decoding the acronym GIS
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GI Systems
GI Sciences
GI Services
Evolution of GIS
GI Systems
• Geographic information system (GIS) is a
system for input, storage, manipulation, and
output of geographic information (NCGIA CC)
• Database system designed to handle
geographically referenced data
• Composed of data, software, hardware, people
and procedure (ESRI)
GI Sciences
• The science behind the technology
• Aimed at enhancing knowledge of geographic concepts
and their computational implementations
• seeks to redefine geographic concepts and their use in
the context of geographic information systems
• Dedicated to the development and use of theories,
methods, technology, and data for understanding
geographic processes, relationships, and pattern
(UCGIS 1994)
GI Services
• Gradual shift from centralized GIS to distributed
GIS
• Examples include location-based service, Webmapping, Web-based planning support system
• GIService is miniature, mobile, public, and taskspecific
• If GISystem is data-centered, GIService is
person-centered
Evolution of GIS
GISystem
GIScience,
Database
• GIScience view
• Database view
GIServices
2. GIScience View
Overcoming limitations of existing GISystem
• Challenges
• Needs
• Subjects of GIScience
Challenges
• Because progress has historically relied on a
fragmented gathering of approaches inherited
from cartography, imposed by hardware, or
borrowed from other computer-related fields, we
are faced with the current situation in which
increased functionality has characteristically
been accompanied by increased conceptual
complexity, making GIS progressively more
nonintuitive for the user.
Representations of space and time by
Donna J. Peuquet, 2002
Needs
• Need better ways to represent, understand, manage,
and communicate our natural world
Subjects of GIScience
• How people think about geographical space and
time
– Ontology of geographic kind
• How to translate human conceptualizations into
formalisms that allow these processes to be
repetitively consistent
– Formalism of spatial language
• How to make people interact more naturally with
information systems
– System design
Egenhofer et al, 1999
• Further readings on GIScience
Goodchild, M.F., 1992, Geographical information science.
International Journal of Geographical Information Systems 6(1): 3145
Goodchild M.F., 1997,What is Geographic Information Science?,
NCGIA Core Curriculum Unit #2
http://www.ncgia.ucsb.edu/giscc/units/u002/
Mark D., 1999, Geographic Information Science: Critical issues in an
emerging cross-disciplinary research domain, workshop on
Geographic Information Science and Geospatial Activities at NSF
http://www.geog.buffalo.edu/ncgia/GIScienceReport.html
3. Database System View
Overcoming limitations of existing DBMS
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Challenges
Needs
Evolutions of DB systems
GIS architecture
SDBMS architecture
Subjects of spatial databases
Challenges
• Previous DBMS is not well accommodated
into geographic concepts as most of
commercial DBMS are designed to handle
attribute data
• What’s special about geographic?  go to
the next slide
Properties of geographic data
• Has location
– Location is a special kind of key (i.e. list of values) how is it handled?
• Multidimensional
– Directional, topological relationships, how is it formalized
• Scale-dependent
– Spatial versus Geographic
• Its occurrence is spatially autocorrelated
– Tobler’s first law of geography
• Not well captured by precise description
– Uncertainty should be formalized
• Some geographic phenomena are continuous
– Object-view wouldn’t fit well
• Some geographic phenomenon is closely associated with temporal
changes
– event, process, moving object
Geographic data need special treatment indeed!
Needs
• We need more constructs to handle spatial
information in order to reduce the
semantic gap between the user’s view of
spatial data and the database
implementation
Spatial Database: a Tour by
Shashi Shekhar and Sanjay Chawla, 2003
Evolution of DB system
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File systems
Network DBMS
Hierarchical DBMS
Relational DBMS
Object-oriented DBMS
Object-relational DBMS
What is object-Relational DBMS?
• Add OO-ness to tables
• All persistent (database) information is still in
tables, but some of the tabular entries can have
richer data structure, that is ADTs
• ORDBMS supports an extended form of SQL
• Potential for mapping spatial concepts
• For example, Oracle 8i implements spatial data
types and spatial operators
GIS architecture
• Built upon File system + Relational DB
– Spatial data is stored in file system
– Attribute data is stored in tables
– Separation between non-spatial and spatial
data
– Specific module for spatial data management
– Also called georelational model
– Examples: Arc/Info, MGE, TiGRis (Intergraph)
GIS architecture
• Built upon relational DB
– Spatial/non-spatial data are stored in tables
– Storing spatial data in table is tedious
– Can hinge on SQL
– Violate data independence principle
– Bad performance
– Difficulty in defining new (spatial) types
GIS architecture
• Built upon object-oriented DB
– Can define user-defined data type (e.g.
ArcGIS geodatabase has different data
models such as hydrology, network, land
parcel, and so on)
– Can define user-defined operations
– Can inherit properties and operations from
superclass
How to map land parcel data?
• In relational database
– e.g. arc/info coverage, arcview shapefile
– spatial data is stored in a file and it’s linked to
attribute data through common attributes
• In object-oriented database
– e.g. arcgis geodatabases
– you can inherit properties from object,
featureclass, polyline and call the methods
area() defined in polyline
Spatial DBMS
• Special kind of DBMS that are specifically
designed to handle spatial data
• Usually seen as middleware (e.g. ArcSDE)
• Can be implemented in either thick or thin client
(e.g. CGI versus Java)
• Have different capabilities depending on which
database models
• Usually support spatial indexing, efficient
algorithms for spatial operations, and domainspecific rules for query optimization
Architecture of SDBMS
Subjects of spatial databases
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Spatial taxonomy
Data model
Query language
Query processing
File organization and indices
Query optimization
Data mining
Review questions
• Discuss the differences between spatial
and nonspatial data
• How can object-relational databases be
used to implement an SDBMS?
• Compare and contrast
– GIS vs. SDBMS
– OODBMS vs. ORDBMS
– GI Systems vs. GI Services
– Querying vs. Data mining