Semantic Web And Databases

The Semantic Web, which is intended to establish a machine-understandable Web, is currently changing from being an emerging trend to a technology used in complex real-world applications. A number of standards and techniques have been developed by the World Wide Web Consortium (W3C), e.g., the Resource Description Framework (RDF), which provides a general method for conceptual descriptions for Web resources, and SPARQL, an RDF querying language. Recent examples of large RDF data with billions of facts include the UniProt comprehensive catalog of protein sequence, function and annotation data, the RDF data extracted from Wikipedia, and Princeton University’s WordNet. Clearly, querying performance has become a key issue for Semantic Web applications. In his book, Groppe details various aspects of high-performance Semantic Web data management and query processing. His presentation fills the gap between Semantic Web and database books, which either fail to take into account the performance issues of large-scale data management or fail to exploit the special properties of Semantic Web data models and queries. After a general introduction to the relevant Semantic Web standards, he presents specialized indexing and sorting algorithms, adapted approaches for logical and physical query optimization, optimization possibilities when using the parallel database technologies of today’s multicore processors, and visual and embedded query languages. Groppe primarily targets researchers, students, and developers of large-scale Semantic Web applications. On the complementary book webpage readers will find additional material, such as an online demonstration of a query engine, and exercises, and their solutions, that challenge their comprehension of the topics presented.

This book constitutes the thoroughly refereed postproceedings of the Second International Workshop on Semantic Web and Databases, SWDB 2004, held in Toronto, Canada in August 2004 as a satellite workshop of VLDB 2004. The 14 revised full papers presented together with 2 papers by the invited keynote speakers were carefully selected during two rounds of reviewing and improvement from 47 submissions. Among the topics addressed are data semantics, semantic Web services, service-oriented computing, workflow composition, XML semantics, relational tables, ontologies, semantic Web algebra, heterogeneous data sources, context mediation, OWL, ontology engineering, data integration, semantic Web queries, database queries, and peer-to-peer warehouses.

Efficient access to data, sharing data, extracting information from data, and making use of the information have become urgent needs for today's corporations. With so much data on the Web, managing it with conventional tools is becoming almost impossible. New tools and techniques are necessary to provide interoperability as well as warehousing betw

Semantic Web Services for Web Databases introduces an end-to-end framework for querying Web databases using novel Web service querying techniques. This includes a detailed framework for the query infrastructure for Web databases and services. Case studies are covered in the last section of this book. Semantic Web Services For Web Databases is designed for practitioners and researchers focused on service-oriented computing and Web databases.

Databases have been designed to store large volumes of data and to provide efficient query interfaces. Semantic Web formats are geared towards capturing domain knowledge, interlinking annotations, and offering a high-level, machine-processable view of information. However, the gigantic amount of such useful information makes efficient management of it increasingly difficult, undermining the possibility of transforming it into useful knowledge. The research presented by De Virgilio, Giunchiglia and Tanca tries to bridge the two worlds in order to leverage the efficiency and scalability of database-oriented technologies to support an ontological high-level view of data and metadata. The contributions present and analyze techniques for semantic information management, by taking advantage of the synergies between the logical basis of the Semantic Web and the logical foundations of data management. The book’s leitmotif is to propose models and methods especially tailored to represent and manage data that is appropriately structured for easier machine processing on the Web. After two introductory chapters on data management and the Semantic Web in general, the remaining contributions are grouped into five parts on Semantic Web Data Storage, Reasoning in the Semantic Web, Semantic Web Data Querying, Semantic Web Applications, and Engineering Semantic Web Systems. The handbook-like presentation makes this volume an important reference on current work and a source of inspiration for future development, targeting academic and industrial researchers as well as graduate students in Semantic Web technologies or database design.

This book constitutes the thoroughly refereed postproceedings of the Second International Workshop on Semantic Web and Databases, SWDB 2004, held in Toronto, Canada in August 2004 as a satellite workshop of VLDB 2004. The 14 revised full papers presented together with 2 papers by the invited keynote speakers were carefully selected during two rounds of reviewing and improvement from 47 submissions. Among the topics addressed are data semantics, semantic Web services, service-oriented computing, workflow composition, XML semantics, relational tables, ontologies, semantic Web algebra, heterogeneous data sources, context mediation, OWL, ontology engineering, data integration, semantic Web queries, database queries, and peer-to-peer warehouses.

An early vision in Computer Science was to create intelligent systems capable of reasoning on larg¬e amounts of data. Independent results in the areas of Semantic Web and Relational Databases have advanced us towards this vision. Despite independent advances, the interface between Relational Databases and Semantic Web is poorly understood. This dissertation revisits this early vision with respect to current technology and addresses the following question: How and to what extent can Relational Databases be integrated with the Semantic Web? The thesis is that much of the existing Relational Database infrastructure can be reused to support the Semantic Web. Two problems are studied. Can a Relational Database be automatically virtualized as a Semantic Web data source? The first contribution is an automatic direct mapping from a Relational Database schema and data to RDF and OWL. The second contribution is a method capable of evaluating SPARQL queries against the Relational Database by exploiting two existing relational query optimizations. These contributions are embodied in the Ultrawrap system. Experiments show that SPARQL query execution performance on Ultrawrap is comparable to that of SQL queries written directly for the relational data. Such results have not been previously achieved. Can a Relational Database be mapped to existing Semantic Web ontologies and act as a reasoner? A third contribution is a method for Relational Databases to support inheritance and transitivity by compiling the ontology as mappings, implementing the mappings as views, using SQL recursion and optimizing by materializing views. Ultrawrap is extended with this contribution. Empirical analysis reveals that Relational Databases are able to effectively act as reasoners.

Databases have been designed to store large volumes of data and to provide efficient query interfaces. Semantic Web formats are geared towards capturing domain knowledge, interlinking annotations, and offering a high-level, machine-processable view of information. However, the gigantic amount of such useful information makes efficient management of it increasingly difficult, undermining the possibility of transforming it into useful knowledge. The research presented by De Virgilio, Giunchiglia and Tanca tries to bridge the two worlds in order to leverage the efficiency and scalability of database-oriented technologies to support an ontological high-level view of data and metadata. The contributions present and analyze techniques for semantic information management, by taking advantage of the synergies between the logical basis of the Semantic Web and the logical foundations of data management. The book’s leitmotif is to propose models and methods especially tailored to represent and manage data that is appropriately structured for easier machine processing on the Web. After two introductory chapters on data management and the Semantic Web in general, the remaining contributions are grouped into five parts on Semantic Web Data Storage, Reasoning in the Semantic Web, Semantic Web Data Querying, Semantic Web Applications, and Engineering Semantic Web Systems. The handbook-like presentation makes this volume an important reference on current work and a source of inspiration for future development, targeting academic and industrial researchers as well as graduate students in Semantic Web technologies or database design.