RDF and RDF Schema are two W3C standards aimed at enriching the Web with machine-processable semantic data.

Real-scale Semantic Web applications, such as Web Portals and E-Marketplaces, require the management of voluminous metadata repositories containing descriptive information (i.e., metadata) about the available Web resources and services. Better knowledge about the meaning, usage, accessibility or quality of these resources and services will considerably facilitate the automated processing of both Web content and services. In this context, the Resource Description Framework (RDF) enables the creation and exchange of metadata as any other Web data. Although large volumes of RDF descriptions are already appearing (e.g., as exported Portal catalogs or service descriptions), sufficiently expressive declarative languages for querying both RDF descriptions and schemas are still missing. In this paper, we propose RQL, a new RDF query language, relying on a formal graph model that permits the interpretation of superimposed resource descriptions. RQL is an OQL-inspired adaptation of XML query languages to the peculiarities of RDF but, foremost, is an extension of this functionality for uniformly querying both descriptions and schemas. We illustrate the syntax, semantics and core functionality of RQL bymeans of a set of benchmark queries and report on the performance of RSSDB, our persistent RDF Store, for storing and querying voluminous RDF descriptions.

RDF and RDF Schema provide the first W3C standard to enrich the Web with machine-processable semantic data. However, to be able to use this semantic data, a scalable, persistent RDF store and a powerful query engine using an expressive query language are needed. Sesame is an extensible architecture implementing both of these. Sesame can be based on arbitrary repositories, ranging from traditional Data Base Management Systems, to dedicated RDF triple stores. Sesame also implements a query engine for RQL, the most powerful RDF/RDF Schema query language to date. 1

This paper investigates that interaction. In particular it studies constraint implication problems, which are important both in understanding the semantics of type/constraint systems and in query optimization. It shows that path constraints interact with types in a highly intricate way. For that purpose a number of results on path constraint implication are established in the presence and absence of type systems. These results demonstrate that adding a type system may in some cases simplify reasoning about path constraints and in other cases make it harder. For example, it is shown that there is a path constraint implication problem that is decidable in PTIME in the untyped context, but that becomes undecidable when a type system is added. On the other hand, there is an implication problem that is undecidable in the untyped context, but becomes not only decidable in cubic time but also finitely axiomatizable when a type system is imposed

Service-based approaches (such as Web Services and the Open Grid Services Architecture) have gained considerable attention recently for supporting distributed application development in e-business and e-science. The emergence of a service-oriented view of hardware and software resources raises the question as to how database management systems and technologies can best be deployed or adapted for use in such an environment. This paper explores one aspect of service-based computing and data management, viz., how to integrate query processing technology with a service-based Grid. The paper describes in detail the design and implementation of a service-based distributed query processor for the Grid. The query processor is service-based in two orthogonal senses: firstly, it supports querying over data storage and analysis resources that are made available as services, and, secondly, its internal architecture factors out as services the functionalities related to the construction of distributed query plans on the one hand, and to their execution over the Grid on the other. The resulting system both provides a declarative approach to service orchestration in the Grid, and demonstrates how query processing can benefit from dynamic access to computational resources on the Grid.

Distributed query processing (DQP) has been widely used in data intensive applications where data of relevance to users is stored in multiple locations. This paper argues: (i) that DQP can be important in the Grid, as a means of providing high-level, declarative languages for integrating data access and analysis

Electronic commerce lets people purchase goods and exchange information on business transactions on-line. Therefore one of the main challenges for the designers of the e-commerce infrastructures is the information sharing, retrieving data located in different sources thus obtaining an integrated view to overcome any contradiction or redundancy. Virtual Catalogs synthesize this approach as they are conceived as instruments to dynamically retrieve information from multiple catalogs and present product data in a unified manner, without directly storing product data from catalogs. In this paper we propose SI-Designer, a support tool for the integration of data from structured and semi-structured data sources, developed within the

We propose a framework for integrating data from multiple relational sources into an XML document that both conforms to a given DTD and satisfies predefined XML constraints. The framework is based on a specification language, AIG, that extends a DTD by (1) associating element types with semantic attributes (inherited and synthesized, inspired by the corresponding notions from Attribute Grammars), (2) computing these attributes via parameterized SQL queries over multiple data sources, and (3) incorporating XML keys and inclusion constraints. The novelty of AIG consists in semantic attributes and their dependency relations for controlling context-dependent, DTD-directed construction of XML documents, as well as for checking XML constraints in parallel with document-generation. We also present cost-based optimization techniques for efficiently evaluating AIGs, including algorithms for merging queries and for scheduling queries on multiple data sources. This provides a new grammar-based approach for data integration under both syntactic and semantic constraints. 1.

View materialization is an important technique for high performance query processing, data integration and replication. Solutions to the problem of incrementally maintaining materialized views are very relevant. So far, most work on this problem has been confined to relational settings and solutions have not been comprehensively evaluated. This paper describes MOVIE, a complete, implemented and evaluated solution to the problem of incrementally maintaining materialized OQL views in ODMG-compliant object databases. The evaluation throws light into how the e#ectiveness of incremental maintenance is a#ected by issues such as database size, and the complexity and selectivity of views.

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