Temporal modules: An approach toward federated temporal databases

X. Sean Wang*, Sushil Jajodia, V. S. Subrahmanian

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

In a federated database environment, different constituents of the federation may use different temporal models or physical representations for the temporal information. This paper introduces a new concept, called a temporal module, to resolve these mismatches among the constituents. Intuitively, a temporal module hides the implementation details of a temporal relation by exposing its information only through two windowing functions: one function associates each time point to a set of tuples and the other function links each tuple with a set of time points. A calculus-style language is given to form queries on temporal modules. Temporal modules are then extended to resolve another type of mismatch among the constituents of a federation, namely, the mismatch involving different time units (e.g., month, week, and day) used in recording temporal information. Our solution to this mismatch relies on "information conversions" provided by each constituent. Specifically, a temporal module is extended to provide several conversion functions; each converts its information to a different time unit. The first step to process a query addressed to the federation is to select suitable conversion functions from the extended temporal modules. In order to do so, time units are formally defined and studied. A federated temporal database model and its query language are proposed. The query language is an extension of the calculus-style language above.

Original languageEnglish (US)
Pages (from-to)103-128
Number of pages26
JournalInformation Sciences
Volume82
Issue number1-2
DOIs
StatePublished - Jan 1995
Externally publishedYes

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications
  • Information Systems and Management
  • Artificial Intelligence

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