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|Title:||Validating semistructured data using OWL||Authors:||Li, Y.F.
|Issue Date:||2006||Citation:||Li, Y.F.,Sun, J.,Dobbie, G.,Sun, J.,Wang, H.H. (2006). Validating semistructured data using OWL. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4016 LNCS : 520-531. ScholarBank@NUS Repository. https://doi.org/10.1007/11775300_44||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 (ORASS) 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. © Springer-Verlag Berlin Heidelberg 2006.||Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)||URI:||http://scholarbank.nus.edu.sg/handle/10635/41701||ISBN:||3540352252||ISSN:||03029743||DOI:||10.1007/11775300_44|
|Appears in Collections:||Staff Publications|
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