XML data warehouses form an interesting basis for decision-support applications that exploit heterogeneous data from multiple sources. However, XML-native database systems currently suffer from limited performances in terms of manageable data volume and response time for complex analytical queries. Fragmenting and distributing XML data warehouses (e.g., on data grids) allow to address both these issues. In this paper, we work on XML warehouse fragmentation. In relational data warehouses, several studies recommend the use of derived horizontal fragmentation. Hence, we propose to adapt it to the XML context. We particularly focus on the initial horizontal fragmentation of dimensions' XML documents and exploit two alternative algorithms. We experimentally validate our proposal and compare these alternatives with respect to a unified XML warehouse model we advocate for.
Pokorn 'y models a XML-star schema in XML by defining dimension hierarchies as sets of logically connected collections of XML data, and facts as XML data elements @cite_7 . H "u mmer propose a family of templates, named XCube, enabling the description of a multidimensional structure (dimension and fact data) for integrating several data warehouses into a virtual or federated warehouse @cite_20 . Rusu propose a methodology, based on the XQuery technology, for building XML data warehouses. This methodology covers processes such as data cleaning, summarization, intermediating XML documents, updating linking existing documents and creating fact tables @cite_4 . Facts and dimensions are represented by XML documents built with XQueries. Park introduce a framework for the multidimensional analysis of XML documents, named XML-OLAP @cite_14 . XML-OLAP is based on an XML warehouse where every fact and dimension is stored as an XML document. The proposed model features a single repository of XML documents for facts and multiple repositories of XML documents for dimensions (one repository per dimension). Eventually, Boussa " d propose an XML-based methodology, named X-Warehousing, for warehousing complex data @cite_6 . They use XML Schema as a modeling language to represent user analysis needs.
@cite_14 @cite_4 @cite_7 @cite_6 @cite_20
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Recently, a large number of XML documents are available on the Internet. This trend motivated many researchers to analyze them multi-dimensionally in the same way as relational data. In this paper, we propose a new framework for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where every fact data as well as dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new multidimensional expression language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate the measure data. They specify text mining operators for aggregating text constituting the measure data. We evaluate XML-OLAP by applying it to a U.S. patent XML warehouse. We use XML-MDX queries, which demonstrate that XML-OLAP is effective for multi-dimensionally analyzing the U.S. patents. A large amount of heterogeneous information is now available in enterprises. Some their data sources are repositories of XML data or they are viewed as XML data independently on their inner implementation. In this paper, we study the foundations of XML data warehouses. We adapt the traditional star schema with explicit dimension hierarchies for XML environment. We propose the notion of XML-referential integrity for handling XML-dimension hierarchies. For querying XML data warehouses, we introduce a semijoin operation based on approximate matching XML data and discuss its effective evaluation. Since the introduction of extensible Markup Language (XML), XML repositories have gained a foothold in many global (and government) organizations, where, e-commerce and e-business models have maturated in handling daily transactional data among heterogeneous information systems in multi-data formats. Due to this, the amount of data available for enterprise decision-making process is increasing exponentially and are being stored and or communicated in XML. This presents an interesting challenge to investigate models, frameworks and techniques for organizing and analyzing such voluminous, yet distributed XML documents for business intelligence in the form of XML warehouse repositories and XML marts. In this paper, we address such an issue, where we propose a view-driven approach for modeling and designing of a Global XML FACT (GxFACT) repository under the MDA initiatives. Here we propose the GxFACT using logically grouped, geographically dispersed, XML document warehouses and Document Marts in a global enterprise setting. To deal with organizations' evolving decision-making needs, we also provide three design strategies for building and managing of such GxFACT in the context of modeling of further hierarchical dimensions and or global document warehouses XML is suitable for structuring complex data coming from different sources and supported by heterogeneous formats. It allows a flexible formalism capable to represent and store different types of data. Therefore, the importance of integrating XML documents in data warehouses is becoming increasingly high. In this paper, we propose an XML-based methodology, named X-Warehousing, which designs warehouses at a logical level, and populates them with XML documents at a physical level. Our approach is mainly oriented to users analysis objectives expressed according to an XML Schema and merged with XML data sources. The resulted XML Schema represents the logical model of a data warehouse. Whereas, XML documents validated against the analysis objectives populate the physical model of the data warehouse, called the XML cube.