Advertisement

A framework for developing temporal databases

  • S. Kokkotos
  • C. D. Spyropoulos
Temporal Databases
Part of the Lecture Notes in Computer Science book series (LNCS, volume 856)

Abstract

Computerised information systems tend to become more sophisticated and complicated. In many application domains, information systems must manage data that change over time, or data that reflect the use of temporal attributes. For these reasons the domain of temporal databases is an active research field. In this paper we present TGDB, a framework for developing temporal database systems that manage both valid and transaction time as well as any kind of user defined time. TGDB offers to the user a relational-like view of the tables and fields, but it is not based on the relational model. Instead it is based on the TGS graph system for time management. TGS combines a very good performance with temporal data management independent from application or domain. The query language of TGDB is an extension of SQL.

Key words

Temporal Databases Time Graph Temporal Data Valid Time Transaction Time 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Ahn I. “Towards an Implementation of Database Management Systems with Temporal Support”, Proceedings of the 2nd International Conference on Data Engineering, IEEE, pp.374–381, 1986.Google Scholar
  2. 2.
    Ahn I., Snodgrass R. “Partitioned Storage for Temporal Databases”, Information Systems, Vol.13, No.4, pp.369–391, 1988.Google Scholar
  3. 3.
    Allen J.F. “Maintaining Knowledge about Temporal Intervals”, Communications of the ACM, Vol.26, No.11, pp.832–843, 1983.Google Scholar
  4. 4.
    Ariav G. “A Temporally Oriented Data Model”, ACM Transactions on Database Systems, Vol.11, No.4, pp.499–527, 1986.Google Scholar
  5. 5.
    Ariav G. “Design Requirements for Temporally Oriented Information Systems”, Proceedings of the IFIP Working Conference on Temporal Aspects in Information Systems, France, pp.3–16, May 1987.Google Scholar
  6. 6.
    Gunadhi H., Segev A. “Efficient Indexing Methods for Temporal Relations”, IEEE Trans. on Knowledge and Data Engineering, Vol.5, No.2, pp.496–509, June 1993.Google Scholar
  7. 7.
    Ioannidis E.V., Kokkotos S., Spyropoulos C.D. “A Temporal Framework for Managing Retroactive and Delayed Updates: An Application to the Payroll Information System of the Greek Public Sector”, European Journal of Information Systems, Vol.2, No.2, pp.149–154, Apr. 1993.Google Scholar
  8. 8.
    Ioannidis E.V., Spyropoulos C.D., Panayiotopoulos T., Skordalakis E. “TIMERx, a Kernel for Managing Temporal References on a RDBMS”, Working Paper, N.C.S.R. “Demokritos”.Google Scholar
  9. 9.
    Kokkotos S., Spyropoulos C.D. “TGS: A Kernel Graph System for Time Management”, Technical Report DEMO 90/6, N.C.S.R. “Demokritos”, June 1990.Google Scholar
  10. 10.
    Kokkotos S., Spyropoulos C.D. “RASS: A ReActive Scheduling System Based on the TGS Kernel”, Proceedings of the AIENG-90 Conference, Boston, MA, pp.523–533, July 1990.Google Scholar
  11. 11.
    Kokkotos S. “Independent Temporal Data Management for Information Systems”, Ph.D. Thesis, Dept. of Electrical Engineering and Computer Engineering, National Technical Univ. of Athens, 1992, (in greek).Google Scholar
  12. 12.
    Lorentzos N., Johnson R.G. “Extending Relational Algebra to Manipulate Temporal Data”, Information Systems,Vol.13, No.3, pp.289–296, 1988.Google Scholar
  13. 13.
    McKenzie E. “Bibliography: Temporal Databases”, ACM SIGMOD RECORD, Vol.15, No.4, pp.40–52, 1986.Google Scholar
  14. 14.
    McKenzie E., Snodgrass R, “Extending the Relational Algebra to Support Transaction Time”, Proceedings of the ACM SIGMOD International Conference on Management of Data, San Fransisco CA, pp.467–479, May 1987.Google Scholar
  15. 15.
    McKenzie E., Snodgrass R. “Supporting Valid Time in a Historical Relational Algebra: Proofs and Extensions, Technical Report TR 91-15, Dept. of Computer Science, Univ. of Arizona, 1991.Google Scholar
  16. 16.
    McKenzie E., Snodgrass R. “Evaluation of Relational Algebras Incorporating the Time Dimension in Databases”, ACM Computing Surveys, Vol.23, No.4, pp.501–543, Dec. 1991.Google Scholar
  17. 17.
    Navathe S.B., Ahmed R. “A Temporal Relational Model and a Query Language”, Information Science, Vol.49, pp.147–175, 1989.Google Scholar
  18. 18.
    Ola A., Ozsoyoglu G. “Incomplete Relational Database Models Based on Intervals”, IEEE Trans. on Knowledge and Data Engineering, Vol.5, No.2, pp.293–308, Apr. 1993.Google Scholar
  19. 19.
    Snodgrass R., Ahn I., “Temporal Databases”, IEEE Computer, Vol.19, No.9, pp.35–42, 1986.Google Scholar
  20. 20.
    Snodgrass R. “The Temporal Query Language TQuel”, ACM Transactions on Database Systems, Vol.12, No.2, pp.247–298, 1987.Google Scholar
  21. 21.
    Soo M.D. “Bibliography on Temporal Databases”, ACM SIGMOD RECORD, Vol.20, No.1, pp.14–23, Mar. 1991.Google Scholar
  22. 22.
    Spyropoulos C.D., Kokkotos S. “Interactive Fuzzy Scheduling Using the Time Graph System TGS”, Proceedings of the AAAI SIGMAN Workshop on Manufacturing Scheduling, IJCAI-89 Conference, Detroit IL, Aug. 1989.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • S. Kokkotos
    • 1
  • C. D. Spyropoulos
    • 1
  1. 1.N.C.S.R. “Demokritos”Aghia ParaskeviGreece

Personalised recommendations