Efficient support of historical queries for multiple lines of evolution

Gad M. Landau, Jeanette P. Schmidt, Vassilis J. Tsotras

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Traditional approaches to history reconstruction problems assume a single line of evolution, i.e., a system (a database, a relation or a collection of objects) evolves over time by applying a set of operations on it. Historical queries are of the form: `find the employees working in a company on January 1st, 1990'. There are however, complex applications where the system's state evolves in a way that results in multiple lines of evolution (such as for example a company that splits into a number of subsidiaries, which on turn may split into new subsidiaries and so on). In general, this creates a tree (hierarchy) of evolution lines, where each node in the tree represents the evolution of a subsidiary. Consider the following (vertical) historical query: `find the employees working for a subsidiary C or one of its ancestors, on January 1st, 1990'; it may well be that C did not yet exist at that time, but it was an ancestor A of C that existed; in this case the answer to the query are the employees of A. Another (horizontal) historical query of interest is the following: given a subsidiary B, `find all the employees which were employed on January 1st, 1990, by subsidiaries which were descendants of B'. This paper focuses on the search parts of these historical queries; several reconstruction methods, designed for single evolution lines may then be used.

Original languageEnglish
Title of host publication1993 IEEE 9th International Conference on Data Engineering
PublisherPubl by IEEE
Number of pages7
ISBN (Print)0818635703
StatePublished - 1993
Externally publishedYes
Event1993 IEEE 9th International Conference on Data Engineering - Vienna, Austria
Duration: 19 Apr 199323 Apr 1993

Publication series

NameProceedings - International Conference on Data Engineering


Conference1993 IEEE 9th International Conference on Data Engineering
CityVienna, Austria

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems


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