The Geometry of Uncertainty in Moving Objects Databases

  • Goce Trajcevski
  • Ouri Wolfson
  • Fengli Zhang
  • Sam Chamberlain
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2287)


This work addresses the problem of querying moving objects databases. which capture the inherent uncertainty associated with the location of moving point objects. We address the issue of modeling, constructing, and querying a trajectories database. We propose to model a trajectory as a 3D cylindrical body. The model incorporates uncertainty in a manner that enables efficient querying. Thus our model strikes a balance between modeling power, and computational efficiency. To demonstrate efficiency, we report on experimental results that relate the length of a trajectory to its size in bytes. The experiments were conducted using a real map of the Chicago Metropolitan area. We introduce a set of novel but natural spatio-temporal operators which capture uncertainty, and are used to express spatio-temporal range queries. We also devise and analyze algorithms to process the operators. The operators have been implemented as a part of our DOMINO project.


Point Query Motion Curve Query Region Move Object Database Chicago Metropolitan Area 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    A. K. Agarwal, L. Arge, and J. Erickson. Indexing moving points. In 19th ACM PODS Conference, 2000.Google Scholar
  2. 2.
    W. Chen, J. Chow, Y. Fuh, J. grandbois, M. Jou, N. Mattos, B. Tran, and Y. Wang. High level indexing of user-defined types. In 25th VLDB Conference, 1999.Google Scholar
  3. 3.
    J. R. Davis. Managing geo-spatial information within the DBMS, 1998. IBM DB2 Spatial Extender.Google Scholar
  4. 4.
    M. Erwig, M. Schneider, and R. H. G üting. Temporal and spatio-temporal datasets and their expressive power. Technical Report 225-12/1997, Informatik berichte, 1997.Google Scholar
  5. 5.
    ESRI. ArcView GIS:The Geographic Information System for Everyone. Environmental Systems Research Institute Inc., 1996.Google Scholar
  6. 6.
    L. Forlizzi, R. H. G üting, E. Nardelli, and M. Schneider. A data model and data structures for moving objects databases. In ACM SIGMOD, 2000.Google Scholar
  7. 7.
    Geographic Data Technology Co. GDT Maps, 2000.
  8. 8.
    V. Graede and O. G ünther. Multidimensional access methods. ACM Computing Surveys, 11(4), 1998.Google Scholar
  9. 9.
    R. H. G üting, M. H. B öhlen, M. Erwig, C. Jensen, N. Lorentzos, M. Schneider, and M. Vazirgiannis. A foundation for representing and queirying moving objects. ACM TODS, 2000.Google Scholar
  10. 10.
    C. M. Hoffman. Solid modeling. In J. E. Goodman and J. O’Rourke, editors, Handbook of Discrete and Computational Geometry. CRC Press, 1997.Google Scholar
  11. 11.
    Intelligent Transportation Systems. ITS maps, 2000.
  12. 12.
    D. Kollios, D. Gunopulos, and V. J. Tsotras. On indexing mobile objects. In 18th ACM PODS Conference, 1999.Google Scholar
  13. 13.
    G. Kollios, D. Gunopulos, and V. J. Tsotras. Nearest neighbour queries in a mobile environment. In STDBM, 1999.Google Scholar
  14. 14.
    M. Kornacker. High-performance extensible indexing. In 25th VLDB Conference, 1999.Google Scholar
  15. 15.
    Oracle Corporation. Oracle8: Spatial Cartridge User’s Guide and Reference, Release 8.0.4, 2000.
  16. 16.
    D. Pfoser and C. Jensen. Capturing the uncertainty of moving objects representation. In SSDB, 1999.Google Scholar
  17. 17.
    D. Pfoser, Y. Theodoridis, and C. Jensen. Indexing trajectories of moving point objects. Technical Report 99/07/03, Dept. of Computer Science, University of Aalborg, 1999.Google Scholar
  18. 18.
    F. P. Preparata and M. I. Shamos. Computational Geometry: an introduction. Springer Verlag, 1985.Google Scholar
  19. 19.
    J. O’Rourke. Computational Geometry in C. Cambridge University Press, 2000.Google Scholar
  20. 20.
    S. Saltenis and C. Jensen. R-tree based indexing of general spatio-temporal data. Technical Report TR-45, TimeCenter, 1999.Google Scholar
  21. 21.
    S. Saltenis and C. Jensen. Indexing of moving objects for location-based services. Technical Report TR-63, TimeCenter, 2001.Google Scholar
  22. 22.
    S. Saltenis, C. S. Jensen, S. T. Leutenegger, and M. A. Lopez. Indexing the positions of continuously moving objects. Technical Report TR-44, TimeCenter, 1999.Google Scholar
  23. 23.
    M. Sharir. Algorithmic motion planning. In J. E. Goodman and J. O’Rourke, editors, Handbook of Discrete and Computational Geometry. CRC Press, 1997.Google Scholar
  24. 24.
    A. P. Sistla, O. Wolfson, S. Chamberlain, and S. Dao. Modeling and querying moving objects. In 13th Int’l Conf. on Data Engineering (ICDE), 1997.Google Scholar
  25. 25.
    A.P. Sistla, P. Wolfson, S. Chamberlain, and S. Dao. Querying the uncertain positions of moving objects. In O. Etzion, S. Jajodia, and S. Sripada, editors, Temporal Databases: Research and Practice. 1999.Google Scholar
  26. 26.
    W. A. Sutherland. Introduction to Metric and Topological Spaces. Oxford University Press, 1998.Google Scholar
  27. 27.
    A. Tansel, J. Clifford, S. Jajodia, A. Segev, and R. Snodgrass. Temporal Databases: Theory and Implementation. Benjamin/ Cummings Publishing Co., 1993.Google Scholar
  28. 28.
    J. Tayeb, O. Ulusoy, and O. Wolfson. A quadtree-based dynamic attribute indexing method. The Computer Journal, 41(3), 1998.Google Scholar
  29. 29.
    Informix Documentation Team. Informix datablade technology: Transforming data into smart data. Informix Press, 1999.Google Scholar
  30. 30.
    Y. Theodoridis, T. Sellis, A. N. Papadopoulos, and Y. Manolopoulos. Specifications for efficient indexing in spatiotemporal databases. In IEEE SSDBM, 1999.Google Scholar
  31. 31.
    Y. Theodoridis, J. R. O. Silva, and M. A. Nascimento. On the generation of spatiotemporal datasets. In 6th Int’l symposium on Large Spatial Databases, 1999.Google Scholar
  32. 32.
    G. Trajcevski, O. Wolfson, and B. Xu. Modeling and querying trajectories of moving objects with uncertainty. Technical Report UIC-EECS-01-2, May 2001.Google Scholar
  33. 33.
    U S Dept. of Commerce. Tiger/Line Census Files: Technical Documentation, 1991.Google Scholar
  34. 34.
    M. Vazirgiannis, Y. Theodoridis, and T. Sellis. Spatiotemporal composition and indexing for large multimedia applications. Multimedia systems, 6(4), 1998.Google Scholar
  35. 35.
    M. Vazirgiannis and O. Wolfson. A spatiotemporal model and language for movign objects on road networks. In SSTD, 2001.Google Scholar
  36. 36.
    O. Wolfson, S. Chamberlain, S. Dao, L. Jiang, and G. Mendez. Cost and imprecision in modeling the position of moving objects. In 14-th ICDE, 1998.Google Scholar
  37. 37.
    O. Wolfson, A. P. Sistla, S. Chamberlain, and Y. Yesha. Updating and querying databases that track mobile units. Distributed and Parallel Databases, 7, 1999.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Goce Trajcevski
    • 1
  • Ouri Wolfson
    • 1
    • 2
  • Fengli Zhang
    • 1
  • Sam Chamberlain
    • 3
  1. 1.Dept. of CSUniversity of Illinois at ChicagoChicago
  2. 2.Mobitrac, Inc.Chicago
  3. 3.Army Research LaboratoryAberdeen Proving Ground

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