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"Querying Wikipedia like a Semantic Database DBpedia is a community effort to extract structured information from Wikipedia and make this information available on the Web. DBpedia allows you to ask sophisticated queries against Wikipedia and to link other datasets on the Web to Wikipedia data."

"he Semantic Web is an extension of the World Wide Web through standards set by the World Wide Web Consortium (W3C).[1] The goal of the Semantic Web is to make Internet data machine-readable. To enable the encoding of semantics with the data, technologies such as Resource Description Framework (RDF)[2] and Web Ontology Language (OWL)[3] are used. These technol"

Wikipedia users constantly revise Wikipedia articles with updates happening almost each second. Hence, data stored in the official DBpedia endpoint can quickly become outdated, and Wikipedia articles need to be re-extracted. DBpedia-Live enables such a continuous synchronization between DBpedia and Wikipedia.

WikipediaMiner is a toolkit for tapping the rich semantics encoded within Wikipedia. It makes it easy to integrate Wikipedia's knowledge into your own applications, by: providing simplified, object-oriented access to Wikipedia's structure and content. measuring how terms and concepts in Wikipedia are connected to each other. detecting and disambiguating Wikipedia topics when they are mentioned in documents.

Linked Data is a method to publish data on the Web and to interlink data between different data sources. Linked Data can be accessed using Semantic Web browsers, just as traditional Web documents are accessed using HTML browsers. However, instead of following document links between HTML pages, Semantic Web browsers enable surfers to navigate between different data sources by following RDF links. RDF links can also be followed by robots or Semantic Web search engines in order to crawl the Semantic Web. See Linked Data - The Story so far and How to publish Linked Data on the Web for more information about Linked Data.

Category:Semantic Web Companies From Wikipedia, the free encyclopedia Companies that embrace semantic web technologies in their products. Pages in category "Semantic Web Companies"

Tagpedia is a semantic reference useful to create sense-based descriptions of resources over the Web. In this way it wants to provide support to a better organization and access to semantically described Web contents in order to improve the management and the search for useful information. The initial contents of Tagpedia has been extracted mining Wikipedia.

The Semantic Web Stack, also known as Semantic Web Cake or Semantic Web Layer Cake, illustrates the architecture of the Semantic Web.

SEMANTIC WEB for the WORKING ONTOLOGIST cuts through the hype around the Semantic Web, providing a simple, feasible, coherent story of a technology that provides real business value today. Authors Allemang and Hendler describe how the Semantic Web builds on the same principles that powered the success of Wikipedia, and of the World Wide Web itself.

The Semantic Wikipedia would combine the properties of the Semantic Web and Wiki technology. In this enhancement, articles would have properties (or traits), which could be mixed or combined to allow articles to be members of dynamic categories, chosen by user requests. Lists would no longer be just the numerous pre-formatted list articles, but rather, a list could be dynamically created for all articles matching selected search properties.

Multimedia Web Ontology Language (MOWL) has been designed to facilitate semantic interactions with multimedia contents. It supports perceptual modeling of concepts using expected media properties. While the reasoning in traditional ontology languages, e.g. Web Ontology Language (OWL), is based on Description Logics, MOWL supports a probabilistic reasoning framework based on Bayesian Network.

"Semantic Web Services, like conventional web services, are the server end of a client-server system for machine-to-machine interaction via the World Wide Web. Semantic services are a component of the semantic web because they use markup which makes data machine-readable in a detailed and sophisticated way (as compared with human-readable HTML which is usually not easily "understood" by computer programs)."

SEMANTIC WEB for the WORKING ONTOLOGIST cuts through the hype around the Semantic Web, providing a simple, feasible, coherent story of a technology that provides real business value today. Authors Allemang and Hendler describe how the Semantic Web builds on the same principles that powered the success of Wikipedia, and of the World Wide Web itself.

A Periodic Update of Semantic Web-related Research using Wikipedia One of the more popular posts of this AI3 blog was a listing of 99 research articles that used Wikipedia in one way or another to do semantic-Web related research.

DBpedia.org is a project aiming to extract structured information from the information creadted as part of the Wikipedia project. This structured information is then made available on the World Wide Web.

Linked Data is about using the Web to connect related data that wasn't previously linked, or using the Web to lower the barriers to linking data currently linked using other methods. More specifically, Wikipedia defines Linked Data as "a term used to describe a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF." This site exists to provide a home for, or pointers to, resources from across the Linked Data community.

Uberblic.org is an integration service for data on the web. It acts as a layer between data publishers and data consumers. It consolidates and reconciles information in real time into a central data repository, and provides developer APIs on top. We make this consolidated data repository available to everyone who needs access to integrated web data, ranging from web developers to large enterprises. The consolidation platform imports information from open data sources like Wikipedia, Geonames, Musicbrainz, TheMovieDB, and others, can mirror changes from these original data sources in real time, and can integrate enterprise data sources into private consolidated views.

The Web Ontology Language (OWL) is a family of knowledge representation languages for authoring ontologies. The languages are characterised by formal semantics and RDF/XML-based serializations for the Semantic Web. OWL is endorsed by the World Wide Web Consortium[1] and has attracted academic, medical and commercial interest.

DBpedia is a project aiming to extract structured information from the information created as part of the Wikipedia project. This structured information is then made available on the World Wide Web. DBpedia allows users to query relationships and properties associated with Wikipedia resources, including links to other related datasets. DBpedia has been described by Tim Berners-Lee as one of the more famous parts of the Linked Data project.