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Validating Semistructured Data Using OWL.

Authors :
Yu, Jeffrey Xu
Kitsuregawa, Masaru
Leong, Hong Va
Li, Yuan Fang
Sun, Jing
Dobbie, Gillian
Sun, Jun
Wang, Hai H.
Source :
Advances in Web-Age Information Management (9783540352259); 2006, p520-531, 12p
Publication Year :
2006

Abstract

Semistructured data has become prevalent in both web applications and database systems. This rapid growth in use makes the design of good semistructured data essential. Formal semantics and automated reasoning tools enable us to reveal the inconsistencies in a semistructured data model and its instances. The Object Relationship Attribute model for Semistructured data (ORA-SS) is a graphical notation for designing and representing semistructured data. This paper presents a methodology of encoding the semantics of ORA-SS in the Web Ontology Language (OWL) and automatically validating the semistructured data design using the OWL reasoning tool - RACER. Our methodology provides automated consistency checking of an ORA-SS data model at both the schema and instance levels. Keywords: Semistructured Data, Semantic Web, OWL, Formal Verification. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540352259
Database :
Complementary Index
Journal :
Advances in Web-Age Information Management (9783540352259)
Publication Type :
Book
Accession number :
32884133
Full Text :
https://doi.org/10.1007/11775300_44