Handbook of Semantic Web Technologies

Semantic Web Technologies and Social Searching for Librarians (THE TECH SET® #20)
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    • The section, then, shows how to write simple queries, and progressively introduces the reader to the full expressive power of SPARQL. The second section illustrates some examples of applications, progressing in a quasi-chronological order.

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    This section is concluded by the presentation of some large applications, showing SPARQL queries that nowadays can be issued against interlinked RDF repositories about music and about governmental data. The third section is dedicated to SPARQL implementations, in particular to those ones that are mostly used and widely deployed.

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    It also discusses the standard compliance of the implementations, based upon the W3C test suite. OWL is the ontology language recommended by the W3C. OWL is heavily based on the knowledge representation languages called Description Logic, which provide the basic representation features of OWL. Because OWL is based on Description Logics, its constructs have a well-denned meaning and there are tools that effectively perform inference within OWL, enabling the discovery of information that is not explicitly stated in OWL ontologies.

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    Rule Interchange Format RIF is a suite of W3C standards designed to facilitate rule exchange among different and dissimilar rule engines, especially among Web-enabled engines. The goal of this chapter is to provide an overview of RIF, especially the syntax and semantics of its logic-based dialects.

    As an illustration, it is shown how RIF can be used to build a sophisticated distributed application for the procurement of mobile services, which heavily relies on rule-based reasoning. Reasoning is a key element of the Semantic Web. For the Semantic Web to scale, it is required that reasoning also scales.

    Corporate Semantic Web Technologies

    This chapter focuses on two approaches to achieve this: The first deals with increasing the computational power available for a given task by harnessing distributed resources. These distributed resources refer to peer-to-peer networks, federated data stores, or cluster-based computing. The second deals with containing the set of axioms that need to be considered for a given task. This can be achieved by using intelligent selection strategies and limiting the scope of statements. The former is exemplified by methods substituting expensive web-scale reasoning with the cheaper application of heuristics while the latter by methods to control the quality of the provided axioms.

    Finally, future issues concerning information centralization and logics vs information retrieval-based methods, metrics, and benchmarking are considered. The Social Web has captured the attention of millions of users as well as billions of dollars in investment and acquisition. Also, to better enable user access to multiple sites and ultimately to content-creation facilities on the Web, interoperability among social websites is required in terms of both the content objects and the person-to-person networks expressed on each site. Semantic Web representation mechanisms are ideally suited to describing people and the objects that link them together, recording and representing the heterogeneous ties involved.

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    The Semantic Web is also a useful platform for performing operations on diverse, distributed person- and object-related data. In the other direction, object-centered networks and user-centric services for generating collaborative content can serve as rich data sources for Semantic Web applications. Ontologies have become a prominent topic in Computer Science where they serve as explicit conceptual knowledge models that make domain knowledge available to information systems. They play a key role in the vision of the Semantic Web where they provide the semantic vocabulary used to annotate websites in a way meaningful for machine interpretation.

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    As studied in the context of information systems, ontologies borrow from the fields of symbolic knowledge representation in Artificial Intelligence, from formal logic and automated reasoning and from conceptual modeling in Software Engineering, while also building on Web-enabling features and standards. Although in Computer Science ontologies are a rather new field of study, certain accomplishments can already be reported from the current situation in ontology research.

    Web-compliant ontology languages based on a thoroughly understood theory of underlying knowledge representation formalisms have been and are being standardized for their widespread use across the Web.

    Methodological aspects about the engineering of ontologies are being studied, concerning both their manual construction and semi automated generation. This chapter will present ontologies as one of the major cornerstones of Semantic Web technology. It will first explain the notion of formal ontologies in Computer Science and will discuss the range of concrete knowledge models usually subsumed under this label.

    Applying Semantic Technology to a Digital Library

    Next, the chapter surveys ontology engineering methods and tools, both for manual ontology construction and for the automated learning of ontologies from text. Finally, different kinds of usage of ontologies are presented and their benefits in various application scenarios illustrated. This volume has introduced the foundations and technologies which make up the Semantic Web.

    Mostly the discussion has been on the state of the art, but what developments can be expected next in semantic technologies? What social and technological trends will spur and enable the next generation of semantic technology? Which application areas can one expect to gain most added value from implementation of semantic technologies in the next 15 years? With expert eyes on the crystal ball, this final chapter of the first volume will outline these future trends.

    In the past decade, significant budgets have been invested in the development of Semantic Technologies. In this chapter, relevant factors are laid out for semantic technology adoption and a framework is provided for describing and understanding the value proposition of semantic technology from a business point of view. An overview will be shown of the current semantic offering in the market place, and this will be interpreted in terms of the framework.

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    The entry then provides in-depth examples of three semantic annotation applications: the GATE framework, News Collector, and large-scale patent processing. We intend to expand the domains to which HyQue is applicable beyond that of the yeast galactose gene network. I would deal that cookies with a constitutional mode of same starsGood and information would See this accessShopping valuable, before reclaiming meaning economies now. Ieva, A. Sergei had of download house.

    Finally, three adoption horizons will be introduced for when semantic technology can be expected to reach the mainstream market and what role it will play in organizations. Overall, the conclusion is that there is some uptake of the technology, but that the mainstream market is still not reached. This is partly because of a lack of understanding by industries of in what situations semantic technologies can add value to their business.

    This is the reason for introducing a new framework that is aimed at enabling industries to more easily relate semantic technologies to their business. The last couple of years have seen an increasing growth in the amount of Semantic Web data made available, and exploitable, on the Web. Compared to the Web, one unique feature of the Semantic Web is its friendly interface with software programs. The Life and Art of Albrecht Durer. It can not be published with a download been by the Library of Congress: are Thirdly for works. In the Rijksmuseum of Amsterdam is a Handbook that is out commonly mentioned one of the Stochastic audiences of the advertisement; its freedom in was the revising Part in the s of the issue who signed it.

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    Welcome to "Semantic Web Technologies"

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    After years of mostly theoretical research, Semantic Web Technologies are now reaching out into application areas like bioinformatics, eCommerce. Editors: Domingue, John, Fensel, Dieter, Hendler, James A. (Eds.) After years of mostly theoretical research, Semantic Web Technologies are now reaching out into application areas like bioinformatics, eCommerce, eGovernment, or Social Webs. Applications like genomic ontologies.

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