Search (7 results, page 1 of 1)

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Abstract

Semantische Mashups sind Anwendungen, die vernetzte Daten aus mehreren Web-Datenquellen mittels standardisierter Datenformate und Zugriffsmechanismen nutzen. Der Artikel gibt einen Überblick über die Idee und Motivation der Vernetzung von Daten. Es werden verschiedene Architekturen und Ansätze zur Generierung von RDF-Daten aus bestehenden Web 2.0-Datenquellen, zur Vernetzung der extrahierten Daten sowie zur Veröffentlichung der Daten im Web anhand konkreter Beispiele diskutiert. Hierbei wird insbesondere auf Datenquellen, die aus sozialen Interaktionen hervorgegangen sind eingegangen. Anschließend wird ein Überblick über verschiedene, im Web frei zugängliche semantische Mashups gegeben und auf leichtgewichtige Inferenzansätze eingegangen, mittels derer sich die Funktionalität von semantischen Mashups weiter verbessern lässt.

Object

Web 2.0

Source

Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini

Theme

Semantic Web

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Abstract

DBpedia is a community effort to extract structured information from Wikipedia and to make this information available on the Web. DBpedia allows you to ask sophisticated queries against datasets derived from Wikipedia and to link other datasets on the Web to Wikipedia data. We describe the extraction of the DBpedia datasets, and how the resulting information is published on the Web for human- and machineconsumption. We describe some emerging applications from the DBpedia community and show how website authors can facilitate DBpedia content within their sites. Finally, we present the current status of interlinking DBpedia with other open datasets on the Web and outline how DBpedia could serve as a nucleus for an emerging Web of open data.

Source

¬The Semantic Web : 6th International Semantic Web Conference, 2nd Asian Semantic Web Conference, ISWC 2007 + ASWC 2007, Busan, Korea, November 11-15, 2007 : proceedings. Ed.: Karl Aberer et al

Theme

Semantic Web

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Abstract

The DBpedia project is a community effort to extract structured information from Wikipedia and to make this information accessible on the Web. The resulting DBpedia knowledge base currently describes over 2.6 million entities. For each of these entities, DBpedia defines a globally unique identifier that can be dereferenced over the Web into a rich RDF description of the entity, including human-readable definitions in 30 languages, relationships to other resources, classifications in four concept hierarchies, various facts as well as data-level links to other Web data sources describing the entity. Over the last year, an increasing number of data publishers have begun to set data-level links to DBpedia resources, making DBpedia a central interlinking hub for the emerging Web of data. Currently, the Web of interlinked data sources around DBpedia provides approximately 4.7 billion pieces of information and covers domains suc as geographic information, people, companies, films, music, genes, drugs, books, and scientific publications. This article describes the extraction of the DBpedia knowledge base, the current status of interlinking DBpedia with other data sources on the Web, and gives an overview of applications that facilitate the Web of Data around DBpedia.

Source

Journal of Web semantics: science, services and agents on the World Wide Web, no.7, S.154-165

Theme

Semantic Web

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Abstract

The degree of structure of Web content is the determining factor for the types of functionality that search engines can provide. The more well structured the Web content is, the easier it is for search engines to understand Web content and provide advanced functionality, such as faceted filtering or the aggregation of content from multiple Web sites, based on this understanding. Today, most Web sites are generated from structured data that is stored in relational databases. Thus, it does not require too much extra effort for Web sites to publish this structured data directly on the Web in addition to HTML pages, and thus help search engines to understand Web content and provide improved functionality. An early approach to realize this idea and help search engines to understand Web content is Microformats, a technique for markingup structured data about specific types on entities-such as tags, blog posts, people, or reviews-within HTML pages. As Microformats are focused on a few entity types, the World Wide Web Consortium (W3C) started in 2004 to standardize RDFa as an alternative, more generic language for embedding any type of data into HTML pages. Today, major search engines such as Google, Yahoo, and Bing extract Microformat and RDFa data describing products, reviews, persons, events, and recipes from Web pages and use the extracted data to improve the user's search experience. The search engines have started to aggregate structured data from different Web sites and augment their search results with these aggregated information units in the form of rich snippets which combine, for instance, data This chapter gives an overview of the topology of the Web of Data that has been created by publishing data on the Web using the microformats RDFa, Microdata and Linked Data publishing techniques.

Source

Semantic search over the Web. Eds.: R. De Virgilio, et al

Theme

Semantic Web

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Abstract

This document provides a tutorial on how to publish Linked Data on the Web. After a general overview of the concept of Linked Data, we describe several practical recipes for publishing information as Linked Data on the Web.

Content

This tutorial has been superseeded by the book Linked Data: Evolving the Web into a Global Data Space written by Tom Heath and Christian Bizer. This tutorial was published in 2007 and is still online for historical reasons. The Linked Data book was published in 2011 and provides a more detailed and up-to-date introduction into Linked Data.

Theme

Semantic Web

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Abstract

The World Wide Web has enabled the creation of a global information space comprising linked documents. As the Web becomes ever more enmeshed with our daily lives, there is a growing desire for direct access to raw data not currently available on the Web or bound up in hypertext documents. Linked Data provides a publishing paradigm in which not only documents, but also data, can be a first class citizen of the Web, thereby enabling the extension of the Web with a global data space based on open standards - the Web of Data. In this Synthesis lecture we provide readers with a detailed technical introduction to Linked Data. We begin by outlining the basic principles of Linked Data, including coverage of relevant aspects of Web architecture. The remainder of the text is based around two main themes - the publication and consumption of Linked Data. Drawing on a practical Linked Data scenario, we provide guidance and best practices on: architectural approaches to publishing Linked Data; choosing URIs and vocabularies to identify and describe resources; deciding what data to return in a description of a resource on the Web; methods and frameworks for automated linking of data sets; and testing and debugging approaches for Linked Data deployments. We give an overview of existing Linked Data applications and then examine the architectures that are used to consume Linked Data from the Web, alongside existing tools and frameworks that enable these. Readers can expect to gain a rich technical understanding of Linked Data fundamentals, as the basis for application development, research or further study.

Content

Inhalt: Introduction - Principles ofLinked Data - The Web ofData - Linked Data Design Considerations - Linked Data Design Considerations - Consuming Linked Data - Summary and Outlook Vgl.: http://linkeddatabook.com/book.

RSWK

Semantic Web / Forschungsergebnis / Forschung / Daten / Hyperlink

Series

Synthesis lectures on the semantic web: theory and technology ; 1

Subject

Semantic Web / Forschungsergebnis / Forschung / Daten / Hyperlink

Theme

Semantic Web

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Abstract

DBpedia Mobile is a location-aware client for the Semantic Web that can be used on an iPhone and other mobile devices. Based on the current GPS position of a mobile device, DBpedia Mobile renders a map indicating nearby locations from the DBpedia dataset. Starting from this map, the user can explore background information about his surroundings by navigating along data links into otherWeb data sources. DBpedia Mobile has been designed for the use case of a tourist exploring a city. As the application is not restricted to a fixed set of data sources but can retrieve and display data from arbitrary Web data sources, DBpedia Mobile can also be employed within other use cases, including ones unforeseen by its developers. Besides accessing Web data, DBpedia Mobile also enables users to publish their current location, pictures and reviews to the Semantic Web so that they can be used by other Semantic Web applications. Instead of simply being tagged with geographical coordinates, published content is interlinked with a nearby DBpedia resource and thus contributes to the overall richness of the Geospatial Semantic Web.

Content

Beitrag anlässlich: Semantic Web Challenge at ISWC 2008, Karlsruhe, Germany, October 2008.