Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration and discuss the difficulties underlying the integration process. We then describe recent progress and identify open research issues. We focus in particular on schema matching, a topic that has received much attention in the database community, but also discuss data matching (for example, tuple deduplication) and open issues beyond the match discovery context (for example, reasoning with matches, match verification and repair, and reconciling inconsistent data values). For previous surveys of database research on semantic integration, see Rahm and Bernstein (2001); Ouksel and Seth (1999); and Batini, Lenzerini, and Navathe (1986).
Description
Semantic-integration research in the database community
%0 Journal Article
%1 1090497
%A Doan, AnHai
%A Halevy, Alon Y.
%C Menlo Park, CA, USA
%D 2005
%I American Association for Artificial Intelligence
%J AI Mag.
%K db integration schema_matching semantic
%N 1
%P 83--94
%T Semantic-integration research in the database community
%U http://portal.acm.org/citation.cfm?id=1090488.1090497
%V 26
%X Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration and discuss the difficulties underlying the integration process. We then describe recent progress and identify open research issues. We focus in particular on schema matching, a topic that has received much attention in the database community, but also discuss data matching (for example, tuple deduplication) and open issues beyond the match discovery context (for example, reasoning with matches, match verification and repair, and reconciling inconsistent data values). For previous surveys of database research on semantic integration, see Rahm and Bernstein (2001); Ouksel and Seth (1999); and Batini, Lenzerini, and Navathe (1986).
@article{1090497,
abstract = {Semantic integration has been a long-standing challenge for the database community. It has received steady attention over the past two decades, and has now become a prominent area of database research. In this article, we first review database applications that require semantic integration and discuss the difficulties underlying the integration process. We then describe recent progress and identify open research issues. We focus in particular on schema matching, a topic that has received much attention in the database community, but also discuss data matching (for example, tuple deduplication) and open issues beyond the match discovery context (for example, reasoning with matches, match verification and repair, and reconciling inconsistent data values). For previous surveys of database research on semantic integration, see Rahm and Bernstein (2001); Ouksel and Seth (1999); and Batini, Lenzerini, and Navathe (1986).},
added-at = {2009-03-13T11:42:53.000+0100},
address = {Menlo Park, CA, USA},
author = {Doan, AnHai and Halevy, Alon Y.},
biburl = {https://www.bibsonomy.org/bibtex/2b64a56c4f1fef347f2a17b00b525a61d/lillejul},
description = {Semantic-integration research in the database community},
interhash = {eee3d65015c0f861805d486582a9ca44},
intrahash = {b64a56c4f1fef347f2a17b00b525a61d},
issn = {0738-4602},
journal = {AI Mag.},
keywords = {db integration schema_matching semantic},
number = 1,
pages = {83--94},
publisher = {American Association for Artificial Intelligence},
timestamp = {2009-03-13T11:42:53.000+0100},
title = {Semantic-integration research in the database community},
url = {http://portal.acm.org/citation.cfm?id=1090488.1090497},
volume = 26,
year = 2005
}