Skip to main content
Log in

A data model for processes based on relative time

  • Published:
Journal of Intelligent Information Systems Aims and scope Submit manuscript

Abstract

Advanced database applications such as automated manufacturing, scheduling, and computer-aided software engineering, demand an explicit representation of processes, including their decomposition into subprocesses, where subprocesses may be repeated or shared. Temporal information on these processes is inherently relative to particular temporal frames of reference, that may be different from that of a complex process containing them. We suggest the Rtime object-oriented data model in which processes are first-class citizens and complex processes are built, using standard type constructors, from their component processes. The relative timing of component processes is a key feature of the suggested model. It allows for a modular construction of complex process objects that may be repeated and shared. Standard object-oriented query languages can be used for temporal queries on processes, by providing an operator for translating timing information between different temporal frames of reference.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Atkinson, M. et al. (1989). The Object-Oriented Database System Manifesto. In Proc. Intl. Conf. on Deductive and Object-Oriented Databases (pp. 40–47). Kyoto, Japan.

  • Allen, J.F. (1983). Maintaining Knowledge about Temporal Intervals. Communications of the ACM, 26(11), 832–843.

    Google Scholar 

  • Bancilhon, F., Cluet, S., and Delobel, C. (1989). A Query Language for the O2 Object-Oriented Database System. In Proc. Second Intl. Workshop on Database Programming Languages, pp. 122–138.

  • Beeri, C. (1989). Formal Models for Object-Oriented Databases. In Proc. First Intl. Conf. on Deductive and Object-oriented databases (pp. 370–395). Kyoto, Japan.

  • Blanken, H. (1991). Implementing Version Support for Complex Objects. Data & Knowledge Engineering, 6, 1–25.

    Google Scholar 

  • Balaban, M. and Murray, N.V. (1989). The Logic of Time Structures: Temporal and Nonmonotonic Features. In Int. Joint Conf. on Artificial Intelligence, pp. 1285–1290.

  • Balaban, M. and Murray, N.V. (1993). Interleaving Time and Structure. To appear in Computers and Artificial Intelligence. Technical Report TR 93–14, Department of Mathematics and Computer Science, Ben-Gurion University, Israel, and Department of Computer Science, SUNYA.

    Google Scholar 

  • Balaban, M. and Samoun, C. (1992). Object-Oriented Music Pieces (oomp)—A First Step in the Formal Conceptualization of Music. In Israeli Symposium on Artificial Intelligence and Computer Vision. Vol. 9.

  • Balaban, M. and Samoun, C. (1993). Hierarchy, Time and Inheritance in Music Modelling. Languages of Design, 1(2).

  • Balaban, M. and Shimony, S.E. (1994). Structured Plans with Sharing and Repetition. Technical Report FC 94–11, Department of Mathematics and Computer Science, Ben-Gurion University, Beer Sheva, Israel. Submitted.

    Google Scholar 

  • Curtis, B., Kellner, M.I., and Over, J. (1992). Process Modelling. Communications of the ACM, 35(9), 75–90.

    Google Scholar 

  • Deux, O. et al. (1991). The O2 System. Communications of the ACM, 34(10), 34–48.

    Google Scholar 

  • Davis, E. (1990). Representations of Commonsense Knowledge, Morgan Kaufmann.

  • Dean, T. (1989). Using Temporal Hierarchies to Efficiently Maintain Large Temporal Databases. Journal of the ACM, pp. 687–718.

  • Elmasri, R. and Wuu, G. (1990). A Temporal Model and Query Language for ER Databases. In Proc. IEEE Data Engineering Conf., pp. 76–83.

  • Foley, J.D. and Van Dam, A. (1982). Fundamentals of Interactive Computer Graphics, Addison Wesley.

  • Forbus, K.D. (1984). Qualitative Process Theory, Ph.D. Thesis, Artificial Intelligence Laboratory, MIT.

  • Gadia, S.K. (1988). A Homogeneous Relational Model and Query Language for Temporal Databases. ACM Transactions on Database Systems, 13(4), 418–448.

    Google Scholar 

  • Hayes, P.J. (1985). The Second Naive Physics Manifesto. In J. Hobbs and B. Moore, (Eds.) Formal Theories of the Commonsense World, Ablex Publishing Corporation, pp. 1–36.

  • Kahn, K. and Gorry, G.A. (1977). Mechanizing Temporal Knowledge. Artificial Intelligence, 9, 87–108.

    Google Scholar 

  • Kemper, A. and Moerkotte, G. (1990). Access Support Relations in Object Bases. In ACM SIGMOD Intl. Conf. on Management of Data, pp. 364–374.

  • Kafer, W. and Schoning, H. (1992). Realizing a Temporal Complex-Object Data Model. In ACM SIGMOD Intl. Conf. on Management of Data, pp. 266–275.

  • Lorentzos, N. and Johnson, R. (1988). Extending Relational Algebra to Manipulate Temporal Data. Information Systems, 13(3), 289–296.

    Google Scholar 

  • Marefat, M., Malhotra, S., and Kashyap, R.L. (1993). Object-Oriented Intelligent Computer-Integrated Design, Process Planning, and Inspection. IEEE Computer, 26(3), 54–65.

    Google Scholar 

  • Maiocchi, R., Pernici, B., and Barbic, F. (1992). Automatic Deduction of Temporal Information. ACM Transactions on Database Systems, 17(4), 647–688.

    Google Scholar 

  • McKenzie, L.E. and Snodgrass, R.T. (1991). Evaluation of Relational Algebras Incorporating the Time Dimension in Databases. ACM Computing Surveys, 23(4), 501–543.

    Google Scholar 

  • Moyne, J.R., Teorey, T.J., and McAfee, L.C.Jr. (1991). Time Sequence Ordering Extensions to the Entity-Relationship Model and Their Application to the Automated Manufacturing Process. Data & Knowledge Engineering, 6, 421–443.

    Google Scholar 

  • Navathe, S.B. and Ahmed, R. (1989). A Temporal Relational Model and a Query Language. Information Systems, 49, 147–175.

    Google Scholar 

  • Pratt, J.M. and Cohen, M. (1992). A Process-Oriented Scientific Database Model. SIGMOD Record, 21(3), 17–25.

    Google Scholar 

  • Ramamritham, K. (1993). Real Time Databases. Distributed and Parallel Databases, 1(2), 199–226.

    Google Scholar 

  • Rose, E. and Segev, A. (1991). TOODM—A Temporal Object-Oriented Data Model with Temporal Constraints. In Intl. Conf. on Entity-Relationship Approach, pp. 205–229.

  • Shuster, A. and Ben-Eliyahu, D. (1993). Rtime Data Model Implementation for the Food Processors Parts Industry of Kibutz Mephalsim. Technical report, Department of Math. and CS, Ben-Gurion University, Beer Sheva, Israel. In Hebrew.

    Google Scholar 

  • Su, S.Y.W. and Chen, H-H.M. (1991). A Temporal Knowledge Representation Model OSAM*/T and Its Query Language OQI/T. In Proc. Intl. Conf. on Very Large Data Bases, pp. 431–442.

  • Snodgrass, R. (1987). The Temporal Query Language TQuel. ACM Transactions on Database Systems, 12(2), 247–298.

    Google Scholar 

  • Snodgrass, R. (1990). Temporal Databases: Status and Research Directions. ACM SIGMOD Record, 19(4), 83–89.

    Google Scholar 

  • Tauzovich, B. (1991). Towards Temporal Extensions to the Entity-Relationship Model. In Intl. Conf. on Entity-Relationship Approach, pp. 163–179.

  • Tuzhilin, A. and Clifford, J. (1991). A Temporal Relational Algebra as a Basis for Temporal Completeness. In Proc. Intl. Conf. on Very Large Data Bases, pp. 13–23.

  • Tansel, A.U. and Garnett, L. (1989). Nested Historical Relations. In ACM SIGMOD Intl. Conf. on Management of Data, pp. 284–293.

  • Theodoulidis, C., Loucopoulos, P., and Wangler, B. (1991). The Entity-Relationship Time Model and the Conceptual Rule Language. In Intl. Conf. on Entity-Relationship Approach, pp. 181–204.

  • Touretzky, D. (1986). The Mathematics of Inheritance Systems. Morgan Kaufmann.

  • Wuu, G.T.J. and Dayal, U. (1992). A Uniform Model for Temporal Object-Oriented Databases. In Proc. IEEE Data Engineering Conf., pp. 584–593.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Balaban, M., Kornatzky, Y. A data model for processes based on relative time. J Intell Inf Syst 7, 29–50 (1996). https://doi.org/10.1007/BF00125521

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00125521

Keywords

Navigation