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The DEDALE System for Complex Spatial Queries.

Stéphane Grumbach, Philippe Rigaux, Luc Segoufin: The DEDALE System for Complex Spatial Queries. SIGMOD Conference 1998: 213-224
@inproceedings{DBLP:conf/sigmod/GrumbachRS98,
  author    = {St{\'e}phane Grumbach and
               Philippe Rigaux and
               Luc Segoufin},
  editor    = {Laura M. Haas and
               Ashutosh Tiwary},
  title     = {The DEDALE System for Complex Spatial Queries},
  booktitle = {SIGMOD 1998, Proceedings ACM SIGMOD International Conference
               on Management of Data, June 2-4, 1998, Seattle, Washington, USA},
  publisher = {ACM Press},
  year      = {1998},
  isbn      = {0-89791-995-5},
  pages     = {213-224},
  ee        = {http://doi.acm.org/10.1145/276304.276324, db/conf/sigmod/GrumbachRS98.html},
  crossref  = {DBLP:conf/sigmod/98},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

This paper presents dedale, a spatial database system intended to overcome some limitations of current systems by providing an abstract and non-specialized data model and query language for the representation and manipulation of spatial objects. dedale relies on a logical model based on linear constraints, which generalizes the constraint database model of [KKR90]. While in the classical constraint model, spatial data is always decomposed into its convex components, in dedale holes are allowed to fit the need of practical applications. The logical representation of spatial data although slightly more costly in memory, has the advantage of simplifying the algorithms. dedale relies on nested relations, in which all sorts of data (thematic, spatial, etc.) are stored in a uniform fashion. This new data model supports declarative query languages, which allow an intuitive and efficient manipulation of spatial objects. Their formal foundation constitutes a basis for practical query optimization. We describe several evaluation rules tailored for geometric data and give the specification of an optimizer module for spatial queries. Except for the latter module, the system has been fully implemented upon the O2 DBMS, thus proving the effectiveness of a constraint-based approach for the design of spatial database systems.

Copyright © 1998 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Laura M. Haas, Ashutosh Tiwary (Eds.): SIGMOD 1998, Proceedings ACM SIGMOD International Conference on Management of Data, June 2-4, 1998, Seattle, Washington, USA. ACM Press 1998, ISBN 0-89791-995-5 BibTeX , SIGMOD Record 27(2), June 1998
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Referenced by

  1. Peter Z. Revesz, Rui Chen, Pradip Kanjamala, Yiming Li, Yuguo Liu, Yonghui Wang: The MLPQ/GIS Constraint Database System. SIGMOD Conference 2000: 601
  2. Luca Forlizzi, Ralf Hartmut Güting, Enrico Nardelli, Markus Schneider: A Data Model and Data Structures for Moving Objects Databases. SIGMOD Conference 2000: 319-330
  3. Floris Geerts, Bart Kuijpers: Linear Approximation of Planar Spatial Databases Using Transitive-Closure Logic. PODS 2000: 126-135
  4. Leonid Libkin: Some Remarks on Variable Independence, Closure, and Orthographic Dimension in Constraint Databases. SIGMOD Record 28(4): 24-28(1999)
  5. Andrew U. Frank, Stéphane Grumbach, Ralf Hartmut Güting, Christian S. Jensen, Manolis Koubarakis, Nikos A. Lorentzos, Yannis Manolopoulos, Enrico Nardelli, Barbara Pernici, Hans-Jörg Schek, Michel Scholl, Timos K. Sellis, Babis Theodoulidis, Peter Widmayer: Chorochronos: A Research Network for Spatiotemporal Database Systems. SIGMOD Record 28(3): 12-21(1999)
  6. Stéphane Grumbach, Philippe Rigaux, Luc Segoufin: On the Orthographic Dimension of Constraint Databases. ICDT 1999: 199-216
  7. Hongjun Zhu, Jianwen Su, Oscar H. Ibarra: An Index Structure for Spatial Joins in Linear Constraint Databases. ICDE 1999: 636-643
  8. Wei Wang, Jiong Yang, Richard R. Muntz: STING+: An Approach to Active Spatial Data Mining. ICDE 1999: 116-125
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