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Virtuoso SPARQL Query Editor

Virtuoso SPARQL Query Editor

Apache Jena - Apache Jena MusicBrainz - The Open Music Encyclopedia S is for Semantics À propos de data.bnf.fr (data.bnf.fr) Current Version This site, which has been available online since July 2011, is continuously being developed and undergoes regular updates. The version currently displayed is Version [1.3] of data.bnf.fr, posted online on 2014/03/25. How to retrieve data from data.bnf.fr: download the data.bnf.fr dump file as of 2014/03/25. Summary: A presentation of the project Roadmap Content and selection policy HTML pagesA new data modelOur data in RDFExternal linksHow does it work? To contact the team:data@bnf.fr A presentation of the project The data.bnf.fr project endeavours to make the data produced by Bibliothèque nationale de France (French National Library) more useful on the Web. With data.bnf.fr, you can: reach BnF resources directly from a Web page, without any previous knowledge of the services provided by the library;get oriented in the BnF resources and possibly find external resources. The objective is to put forward the BnF's collections and to provide a hub between different resources. Roadmap

The Semantic Web in Action - Scientific American - December 2007 Lee Feigenbaum, Ivan Herman, Tonya Hongsermeier, Eric Neumann and Susie Stephens (See sidebar.) Six years ago in this magazine, Tim Berners-Lee, James Hendler and Ora Lassila unveiled a nascent vision of the Semantic Web: a highly interconnected network of data that could be easily accessed and understood by any desktop or handheld machine. They painted a future of intelligent software agents that would head out on the World Wide Web and automatically book flights and hotels for our trips, update our medical records and give us a single, customized answer to a particular question without our having to search for information or pore through results. Since then skeptics have said the Semantic Web would be too difficult for people to understand or exploit. Just below the Surface The Semantic Web is not different from the World Wide Web. Perhaps the most visible examples, though limited in scope, are the tagging systems that have flourished on the Web. Case Study 1: Drug Discovery

DBpedia Un article de Wikipédia, l'encyclopédie libre. DBpedia est un projet universitaire et communautaire d'exploration et extraction automatiques de données dérivées de Wikipédia. Son principe est de proposer une version structurée et sous forme de données normalisées au format du web sémantique des contenus encyclopédiques de chaque fiche encyclopédique. DBpedia vise aussi à relier à Wikipédia (et inversement) des ensembles d'autres données ouvertes provenant du Web des données : DBpedia a été conçu par ses auteurs comme l'un des « noyaux du Web émergent de l'Open data »[2] (connu également sous le nom de Web des données) et l'un de ses possibles points d'entrée. Historique[modifier | modifier le code] Le projet a été lancé par l'université libre de Berlin et l'université de Leipzig, en collaboration avec OpenLink Software. Structure du dépôt de données[modifier | modifier le code] Représentation en carte heuristique des relations entre DBpedia et divers autres projets du Web.

Linked Data - Design Issues Up to Design Issues The Semantic Web isn't just about putting data on the web. It is about making links, so that a person or machine can explore the web of data. Like the web of hypertext, the web of data is constructed with documents on the web. Use URIs as names for things Use HTTP URIs so that people can look up those names. Simple. The four rules I'll refer to the steps above as rules, but they are expectations of behavior. The first rule, to identify things with URIs, is pretty much understood by most people doing semantic web technology. The second rule, to use HTTP URIs, is also widely understood. The third rule, that one should serve information on the web against a URI, is, in 2006, well followed for most ontologies, but, for some reason, not for some major datasets. The basic format here for RDF/XML, with its popular alternative serialization N3 (or Turtle). There is also a large and increasing amount of URIs of non-ontology data which can be looked up. Basic web look-up

Objectifs et élaboration de RDA Ressources : Description et Accès (RDA) est le code de catalogage qui remplace les Règles de catalogage anglo-américaines, 2e éd. (AACR2). Il a été publié en juin 2010, sous la forme d'un site web : RDA Toolkit. (Accès sur abonnement) RDA se présente comme « une nouvelle norme pour la description des ressources et les accès, conçue pour le monde numérique » <>. Il affiche clairement son objectif : prendre en compte le nouvel environnement numérique des catalogues, qu’il s’agisse des ressources décrites, des catalogues eux-mêmes, informatisés et accessibles sur le web, ou des outils mis à la disposition des catalogueurs pour documenter leur travail. Surtout, RDA constitue une initiative essentielle pour rénover les règles de catalogage pour : faire évoluer la structure des catalogues afin de les adapter au contexte actuel de la recherche d’information ; permettre aux catalogues de rendre les services attendus désormais par les usagers. Comment est élaboré RDA ? RDA et l'IFLA

Linked Data Basics for Techies - OpenOrg Intended Audience This is intended to be a crash course for a techie/programmer who needs to learn the basics ASAP. It is not intended as an introduction for managers or policy makers (I suggest looking at Tim Berners-Lee's TED talks if you want the executive summary). It's primarily aimed at people who're tasked with creating RDF and don't have time to faff around. It will also be useful to people who want to work with RDF data. RDF is a data structure perfect for people creating mash-ups! Please Feedback-- especially if something doesn't make sense!!!! If you are new to RDF/Linked Data then you can help me! I put a fair bit of effort into writing this, but I am too familar with the field! If you are learning for the first time and something in this guide isn't explained very well, please drop me a line so I can improve it. cjg@ecs.soton.ac.uk Warning Some things in this guide are deliberately over-simplified. Alternatives (suggest more!) Structure Tree data: (JSON, XML.) Graph data: (RDF). RDFa

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