2,272 research outputs found
Relational Approach to Logical Query Optimization of XPath
To be able to handle the ever growing volumes of XML documents, effective and efficient data management solutions are needed. Managing XML data in a relational DBMS has great potential. Recently, effective relational storage schemes and index structures have been proposed as well as special-purpose join operators to speed up querying of XML data using XPath/XQuery. In this paper, we address the topic of query plan construction and logical query optimization. The claim of this paper is that standard relational algebra extended with special-purpose join operators suffices for logical query optimization. We focus on the XPath accelerator storage scheme and associated staircase join operators, but the approach can be generalized easily
Report on the first Twente Data Management Workshop on XML Databases and Information Retrieval
The Database Group of the University of Twente initiated a new series of workshops called Twente Data Management workshops (TDM), starting with one on XML Databases and Information Retrieval which took place on 21 June 2004 at the University of Twente. We have set ourselves two goals for the workshop series: i) To provide a forum to share original ideas as well as research results on data management problems; ii) To bring together researchers from the database community and researchers from related research fields
Reasoning & Querying – State of the Art
Various query languages for Web and Semantic Web data, both for practical use and as an area of research in the scientific community, have emerged in recent years. At the same time, the broad adoption of the internet where keyword search is used in many applications, e.g. search engines, has familiarized casual users with using keyword queries to retrieve information on the internet. Unlike this easy-to-use querying, traditional query languages require knowledge of the language itself as well as of the data to be queried. Keyword-based query languages for XML and RDF bridge the gap between the two, aiming at enabling simple querying of semi-structured data, which is relevant e.g. in the context of the emerging Semantic Web. This article presents an overview of the field of keyword querying for XML and RDF
Integrating data warehouses with web data : a survey
This paper surveys the most relevant research on combining Data Warehouse (DW) and Web data. It studies the XML
technologies that are currently being used to integrate, store, query, and retrieve Web data and their application to DWs. The paper
reviews different DW distributed architectures and the use of XML languages as an integration tool in these systems. It also introduces
the problem of dealing with semistructured data in a DW. It studies Web data repositories, the design of multidimensional databases for
XML data sources, and the XML extensions of OnLine Analytical Processing techniques. The paper addresses the application of
information retrieval technology in a DW to exploit text-rich document collections. The authors hope that the paper will help to discover
the main limitations and opportunities that offer the combination of the DW and the Web fields, as well as to identify open research
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Bigraphical Logics for XML
Bigraphs have been recently proposed as a meta-model for global computing resources; they are built orthogonally on two structures: a hierarchical ‘place’ graph for locations and a ‘link’ (hyper-)graph for connections. XML is now the standard meta-language for the data exchange and storage on the web. In this paper we address the similarities between bigraphs and XML and we propose bigraphs as a rich model for XML (and XML contexts). Building on this idea we proceed by investigating how the recently proposed logic of BiLog can be instantiated to describe, query and reason about web data (and web contexts)
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