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Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases

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Abstract

Spatio-temporal databases deal with geometries changing over time. In general, geometries cannot only change in discrete steps, but continuously, and we are talking about moving objects. If only the position in space of an object is relevant, then moving point is a basic abstraction; if also the extent is of interest, then the moving region abstraction captures moving as well as growing or shrinking regions. We propose a new line of research where moving points and moving regions are viewed as 3-D (2-D space+time) or higher-dimensional entities whose structure and behavior is captured by modeling them as abstract data types. Such types can be integrated as base (attribute) data types into relational, object-oriented, or other DBMS data models; they can be implemented as data blades, cartridges, etc. for extensible DBMSs. We expect these spatio-temporal data types to play a similarly fundamental role for spatio-temporal databases as spatial data types have played for spatial databases. The paper explains the approach and discusses several fundamental issues and questions related to it that need to be clarified before delving into specific designs of spatio- temporal algebras.

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References

  1. G. Albers and T. Roos. “Voronoi Diagrams of Moving Points in Higher Dimensional Spaces,” 3rd Scandinavian Workshop on Algorithm Theory (SWAT'92), LNCS Vol. 621:399-409, 1992.

  2. K. Al-Taha, R.T. Snodgrass, and M.D. Soo. “Bibliography on Spatio-Temporal Databases,” ACM SIGMOD Record, Vol. 22:59-67, 1994.

    Google Scholar 

  3. A. Belussi, E. Bertino, and B. Catania. “Manipulating Spatial Data in Constraint Databases,” Proc. of the 5th Intl. Symposium on Large Spatial Databases 115-141, Berlin, 1997.

  4. M.H. Böhlen and C. Jensen. Seamless Integration of Time into SQL. Dept. of Computer Science, Aalborg University, Technical Report R-96-49, 1996.

  5. U. Basoglu and J. Morrison. The Efficient Hierarchical Data Structure for the U.S. Historical Boundary File. Harward Papers on GIS, vol. 4, Addison-Wesley, Reading, MA 1978.

    Google Scholar 

  6. J. Clifford and A. Croker. “The Historical Relational Data Model (HRDM) and Algebra Based on Lifespans,” Proc. 3rd Intl. Conf. on Data Engineering, Los Angeles, CA, 1987, 528-537.

  7. J. Chomicki and P.Z. Revesz. “Constraint-Based Interoperability of Spatiotemporal Databases,” Proc. of the 5th Intl. Symposium on Large Spatial Databases, 142-161, Berlin, 1997.

  8. C. Claramunt and M. Thériault. “Managing Time in GIS: An Event-Oriented Approach”. Recent Advances in Temporal Databases, Springer-Verlag, 23-42, 1995.

  9. H. Ehrig and B. Mahr. Fundamentals of Algebraic Specification I. Springer: Berlin, 1985.

    Google Scholar 

  10. J.-J. Fu and R.C.T. Lee. “Voronoi Diagrams of Moving Points in the Plane,” Int. Journal of Computational Geometry and Applications, Vol. 1(1):23-32, 1991.

    Google Scholar 

  11. S.K. Gadia. “A Homogeneous Relational Model and Query Languages for Temporal Databases,” ACM Transactions on Database Systems, Vol. 13:418-448, 1988.

    Google Scholar 

  12. R.H. Güting. “Second-Order Signature: A Tool for Specifying Data Models, Query Processing, and Optimization,” Proc. ACM SIGMOD Conf. 277-286. Washington, 1993

  13. R.H. Güting. “An Introduction to Spatial Database Systems,” VLDB Journal, Vol. 4:357-399, 1994.

    Google Scholar 

  14. R.H. Güting, M.H. Böhlen, M. Erwig, C.S. Jensen, N. Lorentzos, M. Schneider, and M. Vazirgiannis. A Foundation for Representing and Querying Moving Objects. FernUniversität Hagen, Informatik-Report 238, 1998.

  15. S.K. Gadia, V. Chopra, and U.S. Tim. “An SQL-Like Seamless Query of Spatio-Temporal Data,” Int. Workshop on an Infrastructure for Temporal Databases, Q-1-Q-20, 1993.

  16. L. Guibas, J.S.B. Mitchell, and T. Roos. “Voronoi Diagrams of Moving Points in the Plane,” 17th Workshop on Graph-Theoretic Concepts in Computer Science, LNCS Vol. 570: 113-125, 1991.

  17. R.H. Güting, Th. de Ridder, and M. Schneider. “Implementation of the ROSE Algebra: Efficient Algorithms for Realm-Based Spatial Data Types,” Proc. of the 4th Intl. Symposium on Large Spatial Databases, 216-239. Portland, August 1995.

  18. S. Grumbach, P. Rigaux, and L. Segoufin. “The DEDALE System for Complex Spatial Queries,” Proc. ACM SIGMOD Conf., Seattle, 1998, 213-224.

  19. S. Grumbach, P. Rigaux, M. Scholl, and L. Segoufin. “DEDALE, A Spatial Constraint Database,” Proc. Intl. Workshop on Database Programming Languages, 1997.

  20. R.H. Güting and M. Schneider. “Realm-Based Spatial Data Types: The ROSE Algebra,” VLDB Journal, Vol. 4:100-143, 1995.

    Google Scholar 

  21. S.K. Gadia and J.H. Vaishnav. “A Query Language for a Homogeneous Temporal Database,” Proc. ACM Conf. on Principles of Database Systems, 51-56, 1985.

  22. T. Kämpke. “Storing and Retrieving Changes in a Sequence of Polygons,” Int. Journal of Geographical Information Systems, Vol. 8(6):493-513, 1994.

    Google Scholar 

  23. P.C. Kanellakis, G.M. Kuper, and P.Z. Revesz. “Constraint Query Languages,” Proc. 19th Symposium on Principles of Database Systems, 299-313, 1990.

  24. P.C. Kanellakis, G.M. Kuper, and P.Z. Revesz. “Constraint Query Languages,” Journal of Computer and System Sciences, Vol. 51:25-52, 1995.

    Google Scholar 

  25. N. Lorentzos. The Interval-Extended Relational Model and Its Application to Valid-Time Databases. In J. Clifford, S. Gadia, S. Jajodia, A. Segev, and R. Snodgrass (eds.). Temporal Databases: Theory, Design, and Implementation. Benjamin/Cummings Publishing Company, 1993 [38]}, 67-91.

  26. M. Nabil, A. Ngu, and J. Shepherd. “Modeling Moving Objects in Multimedia Database”. Proc. of the 5th Conf. on Database Systems for Advanced Applications, Melbourne, Australia, 1997.

  27. D.J. Peuquet and N. Duan. “An Event-Based Spatiotemporal Data Model (ESTDM) for Temporal Analysis of Geographical Data,” Int. Journal of Geographical Information Systems, Vol. 9(1):7-24, 1995.

    Google Scholar 

  28. F.P. Preparata and M.I. Shamos. Computational Geometry: An Introduction. Springer-Verlag, New York, 1985.

    Google Scholar 

  29. J. Paredaens, J. Van den Bussche, and D. Van Gucht. “Towards a Theory of Spatial Database Queries,” Proc. Symposium on Principles of Database Systems, Minneapolis, 279-288, 1994.

  30. S. Price. “Modeling the Temporal Element in Land Information Systems,” Int. Journal of Geographical Information Systems, Vol. 3(3):233-243, 1989.

    Google Scholar 

  31. H. Raafat, Z. Yang, and D. Gauthier. “Relational Spatial Topologies for Historical Geographical Information,” Int. Journal of Geographical Information Systems, Vol. 8(2):163-173, 1994.

    Google Scholar 

  32. R. Snodgrass. “The Temporal Query Language TQuel,” ACM Transactions on Database Systems, Vol. 12:247-298, 1987.

    Google Scholar 

  33. R. Snodgrass and I. Ahn. “A Taxonomy of Time in Databases,” Proc. ACM SIGMOD Conf., Austin, Texas, 1985, 236-246.

  34. P. Svensson and Z. Huang. “Geo-SAL: A Query Language for Spatial Data Analysis,” Proc. 2nd Intl. Symp. on Large Spatial Databases, Zürich, Switzerland, 1991, 119-140.

  35. A. Segev and A. Shoshani. “Logical Modeling of Temporal Data,” Proc. ACM SIGMOD Conf., San Francisco, 454-466, 1987.

  36. M. Scholl and A. Voisard. “Thematic Map Modeling,” Proc. 1st Intl. Symp. on Large Spatial Databases, Santa Barbara, 167-190, 1989.

  37. A.P. Sistla, O. Wolfson, S. Chamberlain, and S. Dao. “Modeling and Querying Moving Objects,” Proc. IEEE Intl. Conf. on Data Engineering, (Birmingham, U.K., 1997), 422-432.

  38. A.U. Tansel, J. Clifford, S. Gadia, S. Jajodia, A. Segev, and R. Snodgrass (eds.). Temporal Databases: Theory, Design, and Implementation. Benjamin/Cummings Publishing Company, 1993.

  39. L. Vandeurzen, M. Gyssens, and D. Van Gucht. “On the Desirability and Limitations of Linear Spatial Database Models,” Proc. Intl. Symp. on Large Spatial Databases, Portland, Maine, 14-28, 1995.

  40. M. Vazirgiannis, Y. Theodoridis, and T. Sellis. Spatio-Temporal Composition and Indexing for Large Multimedia Applications. To appear in Multimedia Systems, 1997.

  41. M.F. Worboys. “A Unified Model for Spatial and Temporal Information,” The Computer Journal, Vol. 37(1):27-34, 1994.

    Google Scholar 

  42. T.S. Yeh and B. de Cambray. “Time as a Geometric Dimension for Modeling the Evolution of Entities: A 3-D Approach,” 2nd Int. Conf. on Integrating GIS and Environmental Modeling, 1993.

  43. T.S. Yeh and B. de Cambray. “Modeling Highly Variable Spatio-Temporal Data,” 6th AustraliAsian Database Conf., 221-230, 1995.

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Authors and Affiliations

  1. Praktische Informatik IV, Fernuniversita¨t Hagen, D-58084, Hagen, Germany

    Martin Erwig, Ralf Hartmut Gu¨ting, Markus Schneider & Michalis Vazirgiannis

  2. Computer Science Division, Dept. of Electr. and Comp. Engineering, National Tech, University of Athens, Zographou, Athens, 15773, Greece

    Michalis Vazirgiannis

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  1. Martin Erwig
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  2. Ralf Hartmut Gu¨ting
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  3. Markus Schneider
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  4. Michalis Vazirgiannis
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Erwig, M., Gu¨ting, R.H., Schneider, M. et al. Spatio-Temporal Data Types: An Approach to Modeling and Querying Moving Objects in Databases. GeoInformatica 3, 269–296 (1999). https://doi.org/10.1023/A:1009805532638

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