1. Supporting Multiple Representations in Spatio-Temporal Databases Stefano Spaccapietra Database Laboratory Ecole Polytechnique Fédérale Lausanne (EPFL) on behalf of the MurMur Consortium http://lbdwww.epfl.ch

2. 2 Spatio Temporal Evolution of Data Modeling in Databases Expressive power Data Models Codasyl Relational OOER Extended ER UML ODMG Multi- representation

3. 3 Multi-scale Map Production Cartographic Generalization The Database Output Maps

4. 4 Multi-resolution Databases n Cartographic Generalization is costly: -> store the result for reuse How do we express the links between different representations ? -> update propagation

5. 5 Resolution Level 1 Resolution Level 2 Multiple Geometries for the Same Object n One possible solution : stamping spatial attributes with the spatial resolution n Spatial integrity constraints : u Sinuosity (River.geometry[2]) = Sinuosity (River.geometry[1]) u Length (River.geometry[2]) = Length (River.geometry[1]) River described as an area or as a line River mr geo M

6. 6 Multiple Abstraction Levels: aggregation of objects n 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

7. 7 Aggregation Link n 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 FieldBuilding Composed 1,n

8. 8 « Typification » of objects n 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 Ground Building Cartographic Building typify t = ( {1,2,3,4,5}, {a,b,c} )

9. 9 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

10. 10 Classification hierarchy and hierarchical value domains n Describe the same characteristic at different abstraction levels u Hierarchical value domains for attributes u Classification hierarchy for objects cultivated area roseiriscarnation flowercerealoleaginous corn barleyrape sunflower

11. 11 Multi-representation Car Vintage Car Collectible Transport Mean Vehicle Land vehicle Ford Imported Good Movie Accessory

12. 12 Multidimensional Representation Space Classification Space granularity Viewpoint Time granularity two representations of the same object in the same viewpoint at two different resolution levels

13. 13 A Mono-resolution Database Classification Space granularity Viewpoint

14. 14 A Map Classification Space granularity Viewpoint

15. 15 Classification Dimension students faculties persons technicians secretaries Current Status: refinement hierarchies Person FacultyTechnicianSecretary Student Employee facultie s technicians secretaries Is-a

16. 16 Limitation: Roles car-owners companies persons Person Car-owner Company Person-with-car Company-with-car intersection classes partition constraint Car-owner = Person-with-car  Company-with-car Person-with-car  Company-with-car = Ø

17. 17 A More Direct Representation Car-owner OR IS-A Car-ownerCompanyPerson MAY-BE-A + partition constraint Intersection link

18. 18 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

19. 19 Multidimensional Representation Space Classification Space granularity Viewpoint Time granularity How is the representation space - presented to users? - implemented in Ddatabases?

20. 20 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

21. 21 A single schema owner landuse Parcel Building M Cartographic building owner landuse Parcel/use agr/use Parcel/owner Plot Castle composed Typify Road M along near on/under Bridge agr/owner

22. 22 A schema per viewpoint and resolution Local schema : mono resolution and/or mono viewpoint schema Local schema

23. 23 A multi-resolution schema per viewpoint Building M Cartographic building agr/owner owner landuse Parcel/use agr/use Parcel/owner Building M Plot Castle composed Typify Road M along near Parcel Bridge on/under owner Viewpoint 1 Viewpoint 2

24. 24 agr/use A schema per resolution and viewpoint Cartographic building on Building Road Building Castle Plot Bridge Road On / under Parcel/use near Parcel Parcel/owner agr/owner composed

25. 25 An intrinsic schema Intrinsic Schema : description of real world entities independently of any viewpoint Intrinsic schema Local schema

26. 26 Murmur IST Project (2000-2002) n A conceptual data model supporting space, time, and multirepresentation (extension of MADS) n A corresponding query language (multirepresentation algebra) n Two application cases (cartographic, risk assessment) n A schema editor for visual data definition (DDL) n A query editor for visual data manipulation (DML), including intelligent zooming and temporal travelling n Implementation on a GIS (from Star Informatic)

27. 27 The MURMUR Layer Visual Schema Editor Visual Query Language Visual Browser Query by Sketch Tool Murmur Kernel -> OR or OO-> RDBMS-> Open GIS -> GIS Open GIS Wrapper Translation kernel OO/ORDBMS RDBMS GIS STAR Info GIS

28. 28 Murmur : the Consortium n STAR Informatic (GIS provider) n IGN (geodata provider and map producer) n Cemagref (public research center) n Free University Brussels n University of Lausanne n Swiss Federal Institute of Technology Lausanne (EPFL)

29. 29 Contact http://lbdwww.epfl.ch