Effective and Efficient Data Access in the Versatile Web Query Language Xcerpt

Abstract

Access to Web data has become an integral part of many applications and services. In the past, such data has usually been accessed through human-tailored HTML interfaces. Nowadays, rich client interfaces in desktop applications or, increasingly, in browser-based clients ease data access and allow more complex client processing based on XML or RDF data retrieved through Web service interfaces. Convenient specifications of the data processing on the client and flexible, expressive service interfaces for data access become essential in this context. Web query languages such as XQuery, XSLT, SPARQL, or Xcerpt have been tailored specifically for such a setting: declarative and efficient access and processing of Web data. Xcerpt stands apart among these languages by its versatility, i.e., its ability to access not just one Web format but many. In this demonstration, two aspects of Xcerpt are illustrated in detail: The first part of the demonstration focuses on Xcerpt’s pattern matching constructs and rules to enable effective and versatile data access. It uses a concrete practical use case from bibliography management to illustrate these language features. Xcerpt’s visual companion language visXcerpt is used to provide an intuitive interface to both data and queries. The second part of the demonstration shows recent advancements in Xcerpt’s implementation focusing on experimental evaluation of recent complexity results and optimization techniques, as well as scalability over a number of usage scenarios and input sizes.