Skip to main content

Virtual structures — A technique for supporting scientific database applications

  • Conference paper
  • First Online:
Entity-Relationship Approach — ER '94 Business Modelling and Re-Engineering (ER 1994)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 881))

Included in the following conference series:

  • 1241 Accesses

Abstract

Amazonia is based on a comprehensive model that includes a characterization of the development, representation, and evaluation of the concepts employed by scientists in their modeling of both the phenomena of interest and the process of modeling itself. It builds a framework for translating our conceptual model of scientific activity into a simple, unified, computational specification. CML is very simple to use and largely declarative in nature. Virtual R-Structures provide a means of integrating external software tools and smaller code executables (in Fortran, C, Pascal etc.) very easily in the modeling environment. The tool management system provides a generic technique which allows Amazonia to “start” a subsystem (external tool) as a background “server” process and to establish the communication channels between the main system and the server process.

Work supported in part by NSF grant IRI-9117094 and NASA grant NAGW-3888.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. P. Adams and M. Solomon. An Overview of the CAPITL Software Development Environment. Technical Report TR-1143, Computer Science Department, University of Wisconsin-Madison, Apr. 1993.

    Google Scholar 

  2. G. Alonso,A. Saran.A. Sastri,D. Agrawal.A. ElAbbadi,T. R.Smith,and.1. Su. AMAZONIA: A Computational Modeling System for Data-intensive Applications. Technical report, Comp. Sci. Dept., UCSB, 1994.

    Google Scholar 

  3. T. AndrewsandC. Harris. Combining language and database advances in an object-oriented development en vironment. In Proc. Conf. on OOPSLA, pages 430–440,1987.

    Google Scholar 

  4. J. Banerjee, H.-T. Chou, J. F. Garza, W. Kim, D. Woelk, N. Ballou, and H.-J. Kim. Data model issues for object-oriented applications. A CM Trans, on Office Information Systems, 5(1):3–26, 1987.

    Google Scholar 

  5. G. M. Birtwistle, O.-J. Dahl, B. Myhrhaug, and K. Nygaad. SIMULA Begin. Auerbach Press, Philadelphia, PA., 1973.

    Google Scholar 

  6. L. Cardelli. A semantics of multiple inheritance. In G. Kahn, D. MacQueen, and G. Plotkin, editors, Semantics of Data Types, volume 173 of Lecture Notes in Computer Science, pages 51–67. Springer-Verlag, 1984.

    Google Scholar 

  7. L. Cardelli. Structural subtyping and the notion of power types. In Proc. ACM Symp. on Principles of Programming Languages, 1988.

    Google Scholar 

  8. L. Cardelli and P. Wegner. On understanding types, data abstraction, and polymorphism. ACM Comput. Surv., 17(4):471–522, Dec. 1985.

    Google Scholar 

  9. P.-S. Chen. The entity-relationship model — toward a unified view of data. ACM Trans. on Database Systems, 1(1):9–36, 1976.

    Article  Google Scholar 

  10. W. Chu, editor. Proceedings of the NSF Scientific Database Projects, AAAS Workshop on Advances in Data management for the Sicentist and Engineer, Boston, MA., Feb. 1993.

    Google Scholar 

  11. G. Copeland and D. Maier. Making Smalltalk a database system. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1984.

    Google Scholar 

  12. S. de Hoop and P. van Oosterom. Storage and Manipulation of Topology in Postgres. Proceedings of EGIS'92, Munich. Germany, pages 1324–1336, Mar. 1992.

    Google Scholar 

  13. J. Dozier. Looking ahead to EOS: The earth observing system. Computer in Physics, May/June 1990.

    Google Scholar 

  14. EOS: A Mission to Planet Earth, NASA, Washington, D.C., 1990.

    Google Scholar 

  15. N. Hachem, M. Gennert, and M. Ward. The Gaea System: A Spatio-Temporal Database System for Global Change Studies. AAAS Workshop on Adavances in data Management for the Scientist and Engineer, Boston, Massachusetts, USA, pages 84–89, Feb. 1993.

    Google Scholar 

  16. N. Hachem, K. Qiu, M. Gennert, and M. Ward. Managing Derived Data in the Gaea Scientific DBMS. Proceedings of the 19th International Conference on Very Large Databases, Dublin, Ireland, 1993.

    Google Scholar 

  17. M. Hammer and D. McLeod. Database description with SDM: A semantic database model. ACM Trans, on Database Systems, 6(3):351–386, 1981.

    Google Scholar 

  18. J. Hardisty, D. M. Taylor, and S. E. Metcalfe. Computerised Environmental Modelling: a Practical Introduction Using Excel. J. Wiley & Sons, 1993.

    Google Scholar 

  19. Bulletin of the Technical Committee on Data Engineering, 16(1), March 1993. (Special Issue on Scientific Databases).

    Google Scholar 

  20. C. V. Jones. An introduction to graph-based modeling systems, Part I: Overview. ORSA Journal on Computing, 2(2):136–151, 1990.

    Google Scholar 

  21. C. V. Jones. An introduction to graph-based modeling systems, Part II: Graph-grammars and the implementation. ORSA Journal on Computing, 3(3):180–206, 1991.

    Google Scholar 

  22. S. N. Khoshafian and G. P. Copeland. Object identity. In Proc. Conf. on OOPSLA, pages 406–416, 1986.

    Google Scholar 

  23. C. Lecluse, P. Richard, and F. Velez. O2: An object-oriented data model. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 424–433, Chicago, June 1988.

    Google Scholar 

  24. D. Long and et al. REINAS: Real Time Environmental Information Network and Analysis System: Concept Statement. Technical Report, Baskin Centerfor Computer and Information Sciences, University of California at Santa Cruz, UCSC-CRL-93-05, Jan. 1992.

    Google Scholar 

  25. C. B. Medeiros and F. Pires. Databases for GIS. SIGMOD Record, 23(1):107–115, 1994.

    Google Scholar 

  26. J. J. Ordille and B. P. Miller. Database challenges in global information systems. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1993.

    Google Scholar 

  27. H. Paul, H. Schek, M. Scholl, G. Weikum, and U. Deppisch. Architecture and Implementation of the Darmstadt Database Kernel System. Proc. of the SIGMOD International Conference on Management of Data, Snn Francisco, CA, pages 196–206, May 1987.

    Google Scholar 

  28. A. A. G. Requicha. Representations for rigid solids: theory, methods, and systems. Computing Surveys, 12(4):437–464, Dec. 1980.

    Article  Google Scholar 

  29. D. Robertson et al. Eco-Logic: Logic-Based Approaches to Ecological Modelling. MIT Press, Cambridge, Mass., 1991.

    Google Scholar 

  30. A. Saran, K. Park, Y. Chen, A. Aguiar, T. Smith, and J. Su. Developing Applications in CORAL. In International Logic Programming Symposium-Workshop on Programming in Deductive Databases, 1993.

    Google Scholar 

  31. A. Segev. Processing heterogeneous data in scientific databases. In Chu [10].

    Google Scholar 

  32. A. Silberschatz, M. Stonebraker, and J. D. Ullman. Database systems: Achievements and opportunities. ACM SIGMOD Record, 19(4):6–22,Dec. 1990.

    Google Scholar 

  33. T. R. Smith, J. Su, D. Agrawal, and A. El Abbadi. Database and modeling systems for the earth sciences. IEEE Bulletin on Data Engineering, 16(1), 1993.

    Google Scholar 

  34. T. R.Smith.J. Su,D. Agrawal, andA. ElAbbadi. MDBS: A modeling and database systems to support research in the earth sciences. In Chu [10].

    Google Scholar 

  35. T. R. Smith, J. Su, A. El Abbadi, G. Alonso, and A. Saran. Computational modeling systems: Support for the development of scientific models. Technical report, Comp. Sci. Dept., UCSB, 1994.

    Google Scholar 

  36. Design and Implementation of Large Spatial Databases: First Symposium. Springer-Verlag, 1989. Lecture Notes in Computer Science; 409.

    Google Scholar 

  37. Advances in Spatial Databases: 2nd Symposium. Springer-Verlag, 1991. Lecture Notes in Computer Science; 525.

    Google Scholar 

  38. Advances in Spatial Databases: Third International. Symposium. Springer-Verlag, 1993. Lecture Notes in Computer Science; 692.

    Google Scholar 

  39. P. van Oosterom and T. Vijlbrief. Building a GIS on top of the open DBMS Postgres. Proceedings of EGIS'91, Brussels, Belgium, pages 775–787, Apr. 1991.

    Google Scholar 

  40. W.W. and S.H.J. The DASDBS Geo-Kernel — An Extensible Database system for GIS. pages 69–84, 1992. in Three Dimensional Modeling with Geoscientific Information Systems, A.K, Turner (ed.), Kluwer Academic Publishers, Netherlands.

    Google Scholar 

  41. A. Wolf. The DASDBS GEO-Kernel, Concepts, Experiences, and the Second Step. In SSD89 [36]. Lecture Notes in Computer Science; 409.

    Google Scholar 

  42. A. Wolf. How to Fit Geo-Objects into Databases — An Extensibility Approach. Proceedings of the First European Conference on GIS, Amsterdam, Apr. 1990.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Pericles Loucopoulos

Rights and permissions

Reprints and permissions

Copyright information

© 1994 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Smith, T.R., Su, J., Saran, A. (1994). Virtual structures — A technique for supporting scientific database applications. In: Loucopoulos, P. (eds) Entity-Relationship Approach — ER '94 Business Modelling and Re-Engineering. ER 1994. Lecture Notes in Computer Science, vol 881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58786-1_98

Download citation

  • DOI: https://doi.org/10.1007/3-540-58786-1_98

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58786-6

  • Online ISBN: 978-3-540-49100-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics