A Universal-Scheme Approach to Statistical Databases Containing Homogeneous Summary Tables.

@article{DBLP:journals/tods/Malvestuto93,
  author    = {Francesco M. Malvestuto},
  title     = {A Universal-Scheme Approach to Statistical Databases Containing
               Homogeneous Summary Tables},
  journal   = {ACM Trans. Database Syst.},
  volume    = {18},
  number    = {4},
  year      = {1993},
  pages     = {678-708},
  ee        = {http://doi.acm.org/10.1145/169725.169712, db/journals/tods/Malvestuto93.html},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

In many situations a statistical database contains multiple summary tables, which report summary statistics on the same summary variable for the same population of individuals or objects using different classification criteria ("homogeneous" summary tables).

Existing query languages consider only those queries which may aggregate data stored in a single summary table. When a statistical database contains homogeneous summary tables, such query languages do not allow an integrated view of data, whereas statisticans are inclined to view and query a collection of homogeneous summary tables as if they were actually a single higher-dimensional summary table. This legitimizes the search for a universal-scheme solution to the problem of data integration in such statistical databases. It is shown that such a solution can be found if the database tables contain additive summary data. Accordingly, queries are grouped into three classes: queries that can be evaluated to single values (evatuabte queries); queries that can be evaluated to value ranges (answerable queries); and queries whose values remain unknown (unanswerable queries). The membership of a given query to one of these three classes is not an intrinsic property of the query, but depends on both the type of the summary variable and tbe dependencies that are assumed in the universal scheme by the database designer. On the basis of such information, linear-time procedures for recognizing and answering answerable and evaluable queries are developed.

Copyright © 1993 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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Referenced by

1. Carlos A. Hurtado, Alberto O. Mendelzon: Reasoning about Summarizability in Heterogeneous Multidimensional Schemas. ICDT 2001: 375-389
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3. Francesco M. Malvestuto, Marina Moscarini: Computational Issues Connected with the Protection of Sensitive Statistics by Auditing Sum Queries. SSDBM 1998: 134-144
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7. Doron Rotem, J. Leon Zhao: Extendible Arrays for Statistical Databases and OLAP Applications. SSDBM 1996: 108-117
8. Francesco M. Malvestuto, Marina Moscarini: Censoring Statistical Tables to Protect Sensitive Information: Easy and Hard Problems. SSDBM 1996: 12-21
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