Post on 27-Dec-2015
Supporting Multiple Representations
in Spatio-Temporal Databases
Stefano SpaccapietraDatabase Laboratory Ecole Polytechnique Fédérale Lausanne (EPFL)
on behalf of the
MurMur Consortium
http://lbdwww.epfl.ch
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SpatioTemporal
Evolution of Data Modeling in Databases
Expressive power
Data Models
Codasyl
Relational
OOER
Extended ER
UMLODMG
Multi-representation
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Multi-scale Map Production
Cartographic Generalization
The Database Output Maps
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Multi-resolution Databases
Cartographic Generalization is costly:
-> store the result for reuse
How do we express the linksbetween different representations ?-> update propagation
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Resolution Level 1 Resolution Level 2
Multiple Geometries for the Same Object
One possible solution : stamping spatial attributes with the spatial resolution
Spatial integrity constraints : Sinuosity (River.geometry[2]) = Sinuosity (River.geometry[1]) Length (River.geometry[2]) = Length (River.geometry[1])
River described as an area or as a
line
Rivermr geo
M
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Multiple Abstraction Levels: aggregation of objects
Grouping of objects, e.g., according to their spatial relationships Example: a set of buildings close to each other is
replaced with a built-up area
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Aggregation Link Grouping of objects according to
their semantic and spatial relationships e.g., a set of buildings and adjacent
fields belonging to the same farmer grouped into a single object Farm
Derivation of attribute(s): Farm.geometry= Spatial Union
(Field.geometry,Building.geometry)
Aggregation constraint: the fields and the buildings composing the
same farm must belong to the same farmer and the fields must be adjacent.
Farm
Field Building
Composed
Composed
1,n1,n
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« Typification » of objects
Generalization operation (typification): no 1-1 or n-1 mapping between the ground and cartographic buildings
n-m relationship
5 ground buildings (1,2,3,4,5)
represented by 3 cartographic
buildings (a,b,c)
A ground building can participate into 0 or 1 typify relationship
GroundBuildin
g
Cartographic
Buildingtypify
t = ( {1,2,3,4,5} , {a,b,c} )
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Topological Relationships
Level 1
Level 2
At resolution level 1, the road is adjacent to the enbankment.
At resolution level 2, the embankment is no longer represented. The road is seen as adjacent to the building.
Embankment
Road
Near
M
M
M
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Classification hierarchy and hierarchical value domains
Describe the same characteristic at different abstraction levels Hierarchical value domains for attributes Classification hierarchy for objects
cultivated area
rose iriscarnation
flower cereal oleaginous
corn barley rape sunflower
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Multi-representation
Car
Vintage Car
Collectible
Transport Mean
Vehicle
Land vehicle
Ford
Imported GoodMovie Accessory
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Multidimensional Representation Space
Classification
Space granularity
Viewpoint
Time granularity
two representations of the sameobject in the same viewpoint at two different resolutionlevels
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A Mono-resolution Database
Classification
Space granularity
Viewpoint
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A Map
Classification
Space granularity
Viewpoint
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Classification Dimension
students
facultiespersons
technicians
secretaries
• Current Status: refinement hierarchies
Person
Faculty TechnicianSecretary
StudentEmployee
faculties
technicians
secretaries
Is-a
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Limitation: Roles
car-owners companiespersons
Person Car-owner Company
Person-with-car Company-with-carintersectionclasses
partition constraint
Car-owner = Person-with-carCompany-with-car Person-with-car Company-with-car = Ø
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A More Direct Representation
Car-owner
OR IS-ACar-owner CompanyPerson
MAY-BE-A MAY-BE-A
+ partition constraint
Intersection link
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Viewpoint Dimension
Relational DBMS support (mostly non-updatable) views, but semantics is poor
Object-oriented DBMS have rich semantics but poor view mechanisms
Object-relational DBMS: ?
Object-oriented expressiveness augmented with intersection links, roles and revised inheritance rules will provide the best solution
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Multidimensional Representation Space
Classification
Space granularity
Viewpoint
Time granularity
How is the representation space - presented to users?- implemented in Ddatabases?
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Possible architectures
One single multi-resolution, multi-viewpoint schema
One schema per viewpoint and/or per resolution range
One schema per resolution range and per viewpoint
with an intrinsic schema
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A single schema
owner
landuseParcel
Building M
Cartographicbuilding
owner
landuse Parcel/use
agr/use
Parcel/ownerPlot
Castlecomposed
Typify
Road M along
near
on/under
Bridge
agr/owner
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A schema per viewpoint and resolution
Local schema : mono resolution and/or mono viewpoint schema
Local schemaLocal schema
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A multi-resolution schema per viewpoint
Building M
Cartographicbuilding
agr/owner
owner
landuse
landuseParcel/use
agr/use
Parcel/owner
Building MPlot Castlecomposed
Typify
Road M along
near
Parcel
Bridge
on/under
owner
Viewpoint 1
Viewpoint 2
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agr/use
A schema per resolution and viewpoint
Cartographicbuilding
on
Building
Road
Building
Castle
Plot
Bridge
Road
On / under
Parcel/use
near
Parcel Parcel/owneragr/owner
composed
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An intrinsic schema
Intrinsic Schema : description of real world entities independently of any viewpoint
Intrinsic schema
Local schemaLocal schema
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Murmur IST Project (2000-2002)
A conceptual data model supporting space, time, and multirepresentation (extension of MADS)
A corresponding query language (multirepresentation algebra)
Two application cases (cartographic, risk assessment)
A schema editor for visual data definition (DDL)
A query editor for visual data manipulation (DML), including intelligent zooming and temporal travelling
Implementation on a GIS (from Star Informatic)
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The MURMUR Layer
VisualSchemaEditor
VisualQuery
Language
VisualBrowser
Query bySketch
Tool
Murmur Kernel
-> OR or OO -> RDBMS -> Open GIS -> GIS
Open GISWrapper
Translation kernel
OO/ORDBMS RDBMS
GIS
STAR Info
GISGIS
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Murmur : the Consortium
STAR Informatic (GIS provider)
IGN (geodata provider and map producer)
Cemagref (public research center)
Free University Brussels
University of Lausanne
Swiss Federal Institute of Technology Lausanne (EPFL)
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Contact
http://lbdwww.epfl.ch