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Past Indeterminacy in Data Warehouse Design

  • Christina Khnaisser
  • Luc Lavoie
  • Anita Burgun
  • Jean-François EthierEmail author
Conference paper
  • 733 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10439)

Abstract

Traditional data warehouse design methods do not fully address some important challenges, particularly temporal ones. Among them past indeterminacy is not handled systematically and uniformly. Furthermore, most methods published until now present transformation approaches by providing examples rather than general and systematic transformation rules. As a result, real-world applications require manual adaptations and implementations. This hinders scalability, long-term maintenance and increases the risk of inconsistency in case of manual implementation. This article extends the Unified Bitemporal Historicization Framework with a set of specifications and a deterministic process that defines simple steps for transforming a non-historical database schema into a historical schema allowing data evolution and traceability, including past and future indeterminacy. The primary aim of this work is to help data warehouse designers to model historicized schema based on a sound theory ensuring a sound temporal semantic, data integrity and query expressiveness.

Keywords

Data warehouse design Temporal data warehouse Temporal indeterminacy Missing information 

References

  1. 1.
    Allen, J.F.: Maintaining knowledge about temporal intervals. Commun. ACM 26(11), 832–843 (1983)CrossRefzbMATHGoogle Scholar
  2. 2.
    Anselma, L., Piovesan, L., Terenziani, P.: A 1NF temporal relational model and algebra coping with valid-time temporal indeterminacy. J. Intell. Inf. Syst., 1–30 (2015)Google Scholar
  3. 3.
    Anselma, L., Terenziani, P., Snodgrass, R.T.: Valid-time indeterminacy in temporal relational databases: semantics and representations. IEEE Trans. Knowl. Data Eng. 25(12), 2880–2894 (2013)CrossRefGoogle Scholar
  4. 4.
    Arora, S.: A comparative study on temporal database models: a survey. In: 2015 International Symposium on Advanced Computing and Communication (ISACC), pp. 161–167 (2015)Google Scholar
  5. 5.
    Darwen, H., Date, C.J.: The third manifesto. SIGMOD Rec. 24(1), 39–49 (1995)CrossRefGoogle Scholar
  6. 6.
    Date, C.J., Darwen, H.: Database Explorations: Essays on the Third Manifesto and Related Topics. Trafford Publishing, San Francisco (2010)Google Scholar
  7. 7.
    Date, C.J., Darwen, H., Lorentzos, N.A.: Time and relational theory: temporal databases in the relational model and SQL. Morgan Kaufmann, Waltham (2014)Google Scholar
  8. 8.
    Jensen, C.S., et al.: The consensus glossary of temporal database concepts — February 1998 version. In: Etzion, O., Jajodia, S., Sripada, S. (eds.) Temporal Databases: Research and Practice. LNCS, vol. 1399, pp. 367–405. Springer, Heidelberg (1998). doi: 10.1007/BFb0053710 CrossRefGoogle Scholar
  9. 9.
    Jensen, C.S., Soo, M.D., Snodgrass, R.T.: Unifying temporal data models via a conceptual model. Inf. Syst. 19, 513–547 (1993)CrossRefGoogle Scholar
  10. 10.
    Khnaisser, C.: Méthode de construction d’entrepôt de données temporalisé pour un système informationnel de santé. Faculté des sciences, Université de Sherbrooke (2016)Google Scholar
  11. 11.
    Khnaisser, C., Lavoie, L., Burgun, A., Ethier, J.-F.: Unified Bitemporal Historicization Framework. Université de Sherbrooke (GRIIS), Sherbrooke, Québec, Canada (2017)Google Scholar
  12. 12.
    Khnaisser, C., Lavoie, L., Diab, H., Ethier, J.-F.: Data warehouse design methods review: trends, challenges and future directions for the healthcare domain. In: Morzy, T., Valduriez, P., Bellatreche, L. (eds.) ADBIS 2015. CCIS, vol. 539, pp. 76–87. Springer, Cham (2015). doi: 10.1007/978-3-319-23201-0_10 CrossRefGoogle Scholar
  13. 13.
    Rizzi, S., Abello, A., Lechtenborger, J., Trujillo, J.: Research in data warehouse modeling and design: dead or alive? In: 9th ACM International Workshop on Data Warehousing and OLAP – DOLAP 2006, pp. 3–10. Association for Computing Machinery, New York (2006)Google Scholar
  14. 14.
    Snodgrass, R.T.: Developing Time-Oriented Database Applications in SQL. Morgan Kaufmann Publishers, San Francisco (2000)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Christina Khnaisser
    • 1
    • 2
  • Luc Lavoie
    • 1
  • Anita Burgun
    • 2
  • Jean-François Ethier
    • 1
    • 2
    • 3
    Email author
  1. 1.Département d’informatiqueUniversité de SherbrookeSherbrookeCanada
  2. 2.INSERM, UMR 1138 team 22, Centre de Recherche des Cordeliers, Université Paris DescartesParisFrance
  3. 3.Département de médecineUniversité de SherbrookeSherbrookeCanada

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