Validating Semistructured Data Using OWL

نویسندگان

  • Yuan-Fang Li
  • Jing Sun
  • Gillian Dobbie
  • Jun Sun
  • Hai H. Wang
چکیده

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.

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تاریخ انتشار 2006