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

Biodiversity studies in the Ningaloo Reef lagoon

As part of the CSIRO Wealth from Oceans Flagship’s Ningaloo Collaboration Cluster program currently underway in Western Australia, this study aims to examine the habitats and biodiversity of lagoonal areas within Ningaloo Reef. Key habitat types were identified using information from hyperspectral remote sensing and were used to develop a stratified sampling approach. Two focal areas were selected, based on sanctuary zones within Ningaloo Marine Park: Osprey Bay in the north and Coral Bay in the central section; an additional site has recently been added at Gnaraloo in the south. A nested sampling programme was initiated within each location, consisting of surveying transects at different spatial scales: cross-reef transects (shore to back-reef) to identify major habitat types and boundaries between habitats; and finer-scale habitat surveys of biodiversity and abundance of different major groups of organisms, focussing on non-scleractinian cnidarians, macroalgae, sponges, echinoderms and molluscs. Three geomorphological categories have been sampled at each location: back-reef, lagoon and inner reefflat. Ground-truthing was carried out on the extent of habitats along defined transects selected to maximize the diversity of each site. A nested quadrat sampling regime was used to validate remotely-sensed data with field-collected data

Storing and Querying Probabilistic XML Using a Probabilistic Relational DBMS

This work explores the feasibility of storing and querying probabilistic XML in a probabilistic relational database. Our approach is to adapt known techniques for mapping XML to relational data such that the possible worlds are preserved. We show that this approach can work for any XML-to-relational technique by adapting a representative schema-based (inlining) as well as a representative schemaless technique (XPath Accelerator). We investigate the maturity of probabilistic rela- tional databases for this task with experiments with one of the state-of- the-art systems, called Trio

Sample-based XPath Ranking for Web Information Extraction

Web information extraction typically relies on a wrapper, i.e., program code or a configuration that specifies how to extract some information from web pages at a specific website. Manually creating and maintaining wrappers is a cumbersome and error-prone task. It may even be prohibitive as some applications require information extraction from previously unseen websites. This paper approaches the problem of automatic on-the-fly wrapper creation for websites that provide attribute data for objects in a ‘search – search result page – detail page’ setup. The approach is a wrapper induction approach which uses a small and easily obtainable set of sample data for ranking XPaths on their suitability for extracting the wanted attribute data. Experiments show that the automatically generated top-ranked XPaths indeed extract the wanted data. Moreover, it appears that 20 to 25 input samples suffice for finding a suitable XPath for an attribute