An effective data placement strategy for XML documents

As XML is increasingly being used in Web applications, new technologies need to be investigated for processing XML documents with high performance. Parallelism is a promising solution for structured document processing and data placement is a major factor for system performance improvement in parallel processing. This paper describes an effective XML document data placement strategy. The new strategy is based on a multilevel graph partitioning algorithm with the consideration of the unique features of XML documents and query distributions. A new algorithm, which is based on XML query schemas to derive the weighted graph from the labelled directed graph presentation of XML documents, is also proposed. Performance analysis on the algorithm presented in the paper shows that the new data placement strategy exhibits low workload skew and a high degree of parallelism

Mediated data integration and transformation for web service-based software architectures

Service-oriented architecture using XML-based web services has been widely accepted by many organisations as the standard infrastructure to integrate heterogeneous and autonomous data sources. As a result, many Web service providers are built up on top of the data sources to share the data by supporting provided and required interfaces and methods of data access in a unified manner. In the context of data integration, problems arise when Web services are assembled to deliver an integrated view of data, adaptable to the specific needs of individual clients and providers. Traditional approaches of data integration and transformation are not suitable to automate the construction of connectors dedicated to connect selected Web services to render integrated and tailored views of data. We propose a declarative approach that addresses the oftenneglected data integration and adaptivity aspects of serviceoriented architecture

Data integration through service-based mediation for web-enabled information systems

The Web and its underlying platform technologies have often been used to integrate existing software and information systems. Traditional techniques for data representation and transformations between documents are not sufficient to support a flexible and maintainable data integration solution that meets the requirements of modern complex Web-enabled software and information systems. The difficulty arises from the high degree of complexity of data structures, for example in business and technology applications, and from the constant change of data and its representation. In the Web context, where the Web platform is used to integrate different organisations or software systems, additionally the problem of heterogeneity arises. We introduce a specific data integration solution for Web applications such as Web-enabled information systems. Our contribution is an integration technology framework for Web-enabled information systems comprising, firstly, a data integration technique based on the declarative specification of transformation rules and the construction of connectors that handle the integration and, secondly, a mediator architecture based on information services and the constructed connectors to handle the integration process

A Modal Logical Approach for Developing XML Databases

This paper investigates the possibility of realizing the core of an XML database system by a pure modal logical formalism providing query and constraint languages with well-defined syntax semantics and computational elements. The paper also introduces a domain-specific modal logic for XML documents which can be used to implement some of the basic services of an XML database

Content-Aware DataGuides for Indexing Large Collections of XML Documents

XML is well-suited for modelling structured data with textual content. However, most indexing approaches perform structure and content matching independently, combining the retrieved path and keyword occurrences in a third step. This paper shows that retrieval in XML documents can be accelerated significantly by processing text and structure simultaneously during all retrieval phases. To this end, the Content-Aware DataGuide (CADG) enhances the wellknown DataGuide with (1) simultaneous keyword and path matching and (2) a precomputed content/structure join. Extensive experiments prove the CADG to be 50-90% faster than the DataGuide for various sorts of query and document, including difficult cases such as poorly structured queries and recursive document paths. A new query classification scheme identifies precise query characteristics with a predominant influence on the performance of the individual indices. The experiments show that the CADG is applicable to many real-world applications, in particular large collections of heterogeneously structured XML documents