DISTIL: A Design Support Environment for Conceptual Modeling of Spatio-temporal Requirements

  • Sudha Ram
  • Richard T. Snodgrass
  • Vijay Khatri
  • Yousub Hwang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2224)


We describe DISTIL (DIstributed design of SpaTIo-temporaL data), a web-based conceptual modeling prototype system that can help capture the semantics of spatio-temporal data. Via DISTIL, we describe an annotation- based approach that divides spatio-temporal conceptual design into two steps: first capture the current reality of an application using a conventional conceptual model without considering the spatial aspects, and only then annotate the schema with the spatio-temporal semantics of the application. A database development team can use DISTIL to capture and validate their spatio- temporal data requirements. Using DISTIL we demonstrate that the annotation- based approach for capturing spatio-temporal requirements is straightforward to implement, satisfies ontology-based and cognition-based requirements, and integrates seamlessly into the existing database design methodologies.


Existence Time Data Analyst Valid Time Entity Class Transaction Time 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    Y. Bedard, “Visual Modeling of Spatial Databases: Towards Spatial PVL and UML,” Geomatica, Vol. 53, No. 2, pp. 169–186, 1999.Google Scholar
  2. [2]
    C. Bettini, C. E. Dyreson, W. S. Evans, R. T. Snodgrass, and X. S. Wang, “A Glossary of Time Granularity Concepts,” in Temporal Databases: Research and Practice, O. Etzion, S. Jajodia, and S. Sripada, Eds.: Springer-Verlag, 1998, pp. 406–413.Google Scholar
  3. [3]
    P. P. Chen, “The Entity-Relationship Model — Toward a Unified View of Data,” ACM Transactions of Database Systems, Vol. 1, No. 1, pp. 9–36, 1976.CrossRefGoogle Scholar
  4. [4]
    F. A. D’Agnese, C. C. Faunt, A. K. Turner, and M. C. Hill, “Hydrogeologic evaluation and numerical simulation of the Death Valley Regional ground-water flow system, Nevada and California,” U.S. Geological Survey Water Resources 96-4300, 1997.Google Scholar
  5. [5]
    B. David, M. V. D. Herrewegen, and F. Salge, “Conceptual Models for Geometry and Quality of Geographic Information,” in Geographic Objects With Indeterminate Boundaries, P. A. Burrough and A. Frank, Eds.: Taylor & Francis, 1996, pp. 352.Google Scholar
  6. [6]
    C. E. Dyreson and R. T. Snodgrass, “Supporting Valid-Time Indeterminacy,” ACM Transactions on Database Systems, Vol. 23, No. 1, pp. 1–57, 1998.CrossRefGoogle Scholar
  7. [7]
    V. Khatri, S. Ram, and R. T. Snodgrass, “ST-USM: Bridging the Semantic Gap with a Spatio-temporal Conceptual Model,” TIMECENTER Technical Report TR-64 2001.Google Scholar
  8. [8]
    V. Khatri, S. Ram, and R. T. Snodgrass, “Supporting User-defined Granularities and Indeterminacy in a Spatiotemporal Conceptual Model,” Annals of Mathematics and Artificial Intelligence (Also available as TIMECENTER Technical ReportTR-55), 36 pages, forthcoming.Google Scholar
  9. [9]
    G. Kösters and B.-U. Pagel, “The GeoOOA-Tool and Its Interface to Open Software Development Environments for GIS,” in Proceedings of the fourth ACM workshop on Advances on Advances in Geographic Information Systems, Rockville, Maryland, pp. 163–171, 1996.Google Scholar
  10. [10]
    J. L. Mennis, D. J. Peuquet, and L. Qian, “A Conceptual Framework for Incorporating Cognitive Principles into Geographical Database Representation,” International Journal of Geographic Information Science, Vol. 14, No. 6, pp. 501–520, 2000.CrossRefGoogle Scholar
  11. [11]
    C. Parent, S. Spaccapietra, and E. Zimanyi, “Spatio-temporal conceptual models: Data structures + space + time,” in Proceedings of the 7th ACM Symposium on Advances in Geographic Information Systems, Kansas City, USA, pp. 1999.Google Scholar
  12. [12]
    D. Pfoser and N. Tryfona, “Requirements, Definitions, and Notations for Spatiotemporal Application Environments,” in Proceedings of the 6th International Symposium on Advances in Geographic Information Systems, Washington, United States, pp. 124–130, 1998.Google Scholar
  13. [13]
    S. Ram, “Intelligent Database Design using the Unifying Semantic Model,” Information and Management, Vol. 29, No. 4, pp. 191-206, 1995.Google Scholar
  14. [14]
    R. T. Snodgrass and I. Ahn, “Temporal Databases,” IEEE Computer, Vol. 19, No. 9, pp. 35–42, 1986.Google Scholar
  15. [15]
    R. T. Snodgrass, M. H. Böhlen, C. S. Jensen, and A. Steiner, “Adding Transaction Time to SQL/Temporal,” ISO-ANSI SQL/Temporal Change Proposal, ANSI X3H2-96-152r ISO/IEC JTC1/SC21/WG3 DBL MCI-143, 1996.Google Scholar
  16. [16]
    R. T. Snodgrass, M. H. Böhlen, C. S. Jensen, and A. Steiner, “Adding Valid Time to SQL/Temporal,” ISO-ANSI SQL/Temporal Change Proposal, ANSI X3H2-96-151r ISO/IEC JTC1/SC21/WG3 DBL MCI-142, 1996.Google Scholar
  17. [17]
    N. Tryfona and C. S. Jensen, “Conceptual Data Modeling for Spatiotemporal Applications,” Geoinformatica, Vol. 3, No. 3, pp. 245–268, 1999.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Sudha Ram
    • 1
  • Richard T. Snodgrass
    • 1
  • Vijay Khatri
    • 1
  • Yousub Hwang
    • 1
  1. 1.University of ArizonaUSA

Personalised recommendations