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On the organization of large shared Model bases

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Abstract

Central to the Model Management (MM) function is the creation and maintenance of a knowledge-based model repository. The Model Knowledge Base (MKB) provides the basis by which information about models can be shared to facilitate consistent and controlled utilization of existing models for decision making, as well as the development of new models. Various schemes for representing individual models have been proposed in the literature. This paper focuses on how best to structure, control, and administer a large MKB to support organization-wide modeling activities. Guided by a recently proposed systems framework for MM, we describe a number of concepts which are useful for capturing the semantics and structural relationships of models in an MKB. These concepts, and the nature of the MMS functions to be supported, are then used to derive specific information management requirements for model bases. Four major requirements are identified: (1) management of composite model configurations; (2) management of model version histories; (3) support for the model consultation and selection functions of an MMS; and (4) support for multiple logical MKBs (private, group, and public). We argue that traditional record-based approaches to data management appear to fall short of capturing the rich semantics present in an MM environment. The paper proposes an architecture for an MMS, focusing on its major component — the MKB Management Subsystem. An implementation of this architecture is briefly described.

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References

  1. L.M. Applegate, G. Klien, B.R. Konsynski and J.F. Nunamaker, Model management systems: Proposed model representations and future designs,Proc. 6th Int. Conf. on Information Systems (December, 1985), pp. 1–16.

  2. L.M. Applegate, B.R. Konsynski and J.F. Nunamaker, Model management systems: Designs for decision support, Decision Support Syst. 2(1986)81–91.

    Google Scholar 

  3. D. Batory, J. Barnett, J. Garza, K. Smith, K. Tsukuda and T. Wise, GENESIS: A reconfigurable database management system, Technical Report TR-86-07, Department of Computer Science, University of Texas at Austin (March 1986).

  4. H.K. Bhargava, M. Bieber and S.O. Kimbrough, Oona, Max and the WYWWYWI principle: Generalized hypertext and model management in a symbolic programming environment,Proc. 9th Int. Conf. on Information Systems (December 1988), pp. 179–191.

  5. H.K. Bhargava and R. Krishnan, A formal approach for model formulation in a model management system,Proc. 23rd Annual Hawaii Int. Conf. on System Sciences (January 1990).

  6. R.W. Blanning, Data management and model management: A relational synthesis,Proc. ACM 20th Annual Southeast Regional Conf. (April 1982), pp. 139–147.

  7. R.W. Blanning, A relational framework for join implementation in model management systems, Decision Support Syst. 1(1985)69–81.

    Google Scholar 

  8. R.H. Bonczek, C.W. Holsapple and A.B. Whinston,Foundations of Decision Support Systems (Academic Press, New York, 1981).

    Google Scholar 

  9. G.E.P. Box and G.M. Jenkins,Time Series Analysis: Forecasting and Control (Holden-Day, 1970).

  10. M.J. Carey and D.J. DeWitt, Extensible database systems,Proc. Islamorada Workshop on Large Scale Knowledge Base and Reasoning Systems (February 1985).

  11. M.J. Carey and D.J. DeWitt, An overview of the EXODUS project, Database Eng. 10(2) (1987) 47–54.

    Google Scholar 

  12. P.P.S. Chen, The entity-relationship model: Toward a unified view of data, ACM Trans. Database Syst. 1(1976)9–36.

    Google Scholar 

  13. E.F. Codd, Extending the database relational model to capture more meaning, ACM Trans. Database Syst. 4(1979)397–434.

    Google Scholar 

  14. B. Dimsdale and H.M. Markowitz, A description of the SIMSCRIPT language, IBM Syst. J. 3(1964) 57–67.

    Google Scholar 

  15. D.R. Dolk and B.R. Konsynski, Knowledge representation for model management systems, IEEE Trans. Software Eng. SE-10(1984)619–628.

    Google Scholar 

  16. A. Dutta and A. Basu, An artificial intelligence approach to model management in decision support systems, IEEE Comput. 19(1984)89–97.

    Google Scholar 

  17. J.J. Elam, J.C. Henderson and L.W. Miller, Model management systems: An approach to decision support in complex organizations,Proc. 1st Int. Conf. on Information Systems (December 1980), pp. 98–110.

  18. K.P. Eswaran, A general purpose trigger subsystem and its inclusion in a relational database system, Technical Report TR-86-07, IBM Research Laboratory, San Jose, CA (July 1986).

    Google Scholar 

  19. J. Fedorowicz and G.B. Williams, Representing modeling knowledge in an intelligent decision support system, Decision Support Syst. 2(1986)3–14.

    Google Scholar 

  20. A.M. Geoffrion, An introduction to structured modeling, Manag. Sci. 33(1987)547–588.

    Google Scholar 

  21. A.M. Geoffrion, The SML language for structured modeling, Working Paper No. 378, Western Management Science Institute, University of California, Los Angeles (August, 1990).

    Google Scholar 

  22. H.J. Greenberg, A functional description of ANALYZE: A computer-assisted analysis system for linear programming models, ACM Trans. Math. Software 9(1983)18–56.

    Google Scholar 

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

    Google Scholar 

  24. R.L. Haskin and R.A. Lorie, On extending the functions of a relational database system,Proc. ACM SIGMOD Conf. (June 1982), pp. 207–212.

  25. C.W. Holsapple and A.B. Whinston, Model management issues and directions, Working Paper No. 7, Department of Decision Science and Information Systems, University of Kentucky (November 1988).

  26. R.H. Katz,Information Management for Engineering Design (Springer, 1985).

  27. W. Kent, Limitations of record-based information models, ACM Trans. Database Syst. 4(1979) 107–131.

    Google Scholar 

  28. W. Kent, Consequences of assuming a universal relation, ACM Trans. Database Syst. 6(1981) 539–556.

    Google Scholar 

  29. J.L. King, Centralized versus decentralized computing: Organizational considerations and management options, ACM Comput. Surveys 15(1983)319–349.

    Google Scholar 

  30. R. Krishnan, A logic modeling language for automated model construction, Decision Support Syst. 6(1990)123–152.

    Google Scholar 

  31. T.-P. Liang, Integrating model management with data management in decision support systems, Decision Support Syst. 1(1985)221–232.

    Google Scholar 

  32. T.-P. Liang, Toward the development of a knowledge-based model management system, Working Paper, Department of Decision Sciences, The Wharton School, University of Pennsylvania, Philadelphia, PA (January 1986).

    Google Scholar 

  33. T.-P. Liang, Development of a knowledge-based model management system, Oper. Res. 36(1988) 849–863.

    Google Scholar 

  34. M.V. Mannino, B.S. Greenberg and S.N. Hong, Model libraries: Knowledge representation and reasoning, ORSA J. Comput. 2(1990)287–301.

    Google Scholar 

  35. L.W. Miller and N. Katz, Model management systems to support policy analysis, Decision Support Syst. 2(1986)55–63.

    Google Scholar 

  36. W.A. Muhanna, A systems framework for model management in organizations, Ph.D. Dissertation, University of Wisconsin-Madison (December 1987).

  37. W.A. Muhanna and R.A. Pick, Composite models in SYMMS,Proc. 21st Annual Hawaii Int. Conf. on System Sciences (January 1988), pp. 418–427.

  38. W.A. Muhanna and R.A. Pick, Meta-modeling concepts and tools for model management: A systems approach, Working Paper No. 91-1, College of Business, The Ohio State University (1990), submitted.

  39. W.A. Muhanna, Issues in distributed model management systems,Proc. 11th Annual Int. Conf. on Information Systems (December 1990), pp. 231–242.

  40. W.A. Muhanna, An object-oriented framework for model management and DSS development,Proc. 1st ISDAA Conf. (September 1990), pp. 553–565.

  41. W.A. Muhanna, SYMMS: Design and implementation notes, Working Paper, The Ohio State University (1990).

  42. F.H. Murphy and E.A. Stohr, An intelligent system for formulating linear programs, Decision Support Syst. 2(1986)39–47.

    Google Scholar 

  43. S.-S. Pan, R.A. Pick and A.B. Whinston, A formal approach to decision support, in:Management and Office Information Systems, ed. S.K. Chang (Plenum Press, 1984).

  44. R.A. Pick and M. Sklar, A knowledge engineered linear programming formulation assistant,Proc. 23rd Annual Hawaii Int. Conf. on System Sciences (January 1990), pp. 269–278.

  45. D.M. Ritchie and K. Thompson, The UNIX time-sharing system, Bell Syst, Tech. J. 57(1978) 1905–1929.

    Google Scholar 

  46. M.J. Rochkind, The source code control system, IEEE Trans. Software Eng. SE-1(1975).

    Google Scholar 

  47. M.J. Shaw, P.-L. Tu and P. De, Applying machine learning to model management in decision support systems, Decision Support Syst. 4(1988)285–305.

    Google Scholar 

  48. J.M. Smith and D.C.P. Smith, Database abstractions: Aggregation and generalization, ACM Trans. Database Syst. 2(1977)105–133.

    Google Scholar 

  49. R.H. Sprague and E.D. Carlson,Building Effective Decision Support Systems (Prentice-Hall, Englewood Cliffs, NJ, 1982).

    Google Scholar 

  50. E.A. Stohr and M. Tanniru, A database for operations research models, Int. J. Policy Anal. Info. Syst. 4(1980)105–121.

    Google Scholar 

  51. M. Stonebraker, Triggers and inference in database systems, Memorandum No. UCB/ERL M85/46, Electronics Research Laboratory, College of Engineering, University of California, Berkeley (May 1985).

    Google Scholar 

  52. M. Stonebraker, B. Rubenstein and A. Guttman, Application of abstract data types and abstract indices to CAD databases,Proc. 1983 ACM Engineering Design Applications (May 1983), pp. 107–114.

  53. M. Stonebraker and L.A. Row, The design of POSTGRES,Proc. 1986 SIGMOD Conf. (May 1986).

  54. T. Teitelbaum and T. Reps, The Cornell program synthesizer: A syntax-directed programming environment, Commun. ACM 24(1981)563–573.

    Google Scholar 

  55. W.F. Tichy, Design, implementation, and evaluation of a revision control system,Proc. 6th Int. Conf. on Software Design, IEEE (September 1982), pp. 58–67.

  56. E. Turban,Decision Support and Expert Systems: Management Support Systems (Macmillan, New York, 1988).

    Google Scholar 

  57. J.S. Welch, Jr., PAM — A practitioner's approach to modeling, Manag. Sci. 33(1987)610–625.

    Google Scholar 

  58. H.J. Will, Model management systems, in:Information Systems and Organization Structure, ed. E. Grochla and N. Szyperski (Walter de Gruyter, Berlin, 1975).

    Google Scholar 

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Muhanna, W.A. On the organization of large shared Model bases. Ann Oper Res 38, 359–396 (1992). https://doi.org/10.1007/BF02283658

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