Mining XML Schemas to Extract Conceptual Knowledge

Mining XML Schemas to Extract Conceptual Knowledge

Ivan Bedini (Alcatel-Lucent Bell Labs, Ireland), Benjamin Nguyen (University of Versailles, France), Christopher Matheus (Alcatel-Lucent Bell Labs, Ireland), Peter F. Patel-Schneider (Alcatel-Lucent Bell Labs, USA) and Aidan Boran (Alcatel-Lucent Bell Labs, Ireland)
Copyright: © 2012 |Pages: 27
DOI: 10.4018/978-1-4666-0188-8.ch004
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One of the promises of the Semantic Web is to support applications that easily and seamlessly deal with heterogeneous data. Most data in the Web, however, is in the Extensible Markup Language (XML) format, but using XML requires applications to understand the format of each data source that they access. Achieving the benefits of the Semantic Web involves transforming XML into the Semantic Web languages, OWL (the Web Ontology Language) and RDF (the Resource Description Framework), a process that generally has manual or only semi-automatic components. In this chapter, the authors present a set of patterns that enable the automatic transformation from XML Schema into RDF and OWL, enabling the direct use of much XML data in the Semantic Web. They focus on a possible logical representation of the first language and present an implementation, including a comparison with related works.
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Xml Documents And Xml Schemas

An XML Schema (Fallside, 2004) formally describes what a given XML document (Bray, 2008) contains, in the same way a database schema describes the data that can be contained in a database (tree structures, data types, integrity constraints, etc.). An XML Schema describes the coarse shape of the XML document. It can be used to express a set of rules to which an XML document must conform to be considered as 'valid' according to that schema, as depicted in Figure 1. Rules can define what fields or sub-element an element can contain. An XML Schema can also describe the values that can be placed into any element or attribute. At present, there exist several XML languages to describe XML documents.

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