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(LOV) Linked Open Vocabularies

(LOV) Linked Open Vocabularies

XML vs RDF : logique structurelle contre logique des données XML et RDF sont deux modèles différents d'encodage de l'information et, pourtant, ils sont souvent confondus. Le dernier exemple en date est la mise à disposition par la British Library de 14 millions de notices bibliographiques au format, je cite, « RDF/DC ». La confusion est patente de par l'absence d'URI pour identifier les ressources décrites. Or, en tant que lecteur régulier de ce blog, vous savez que l'URI est un des fondements du modèle RDF. Il est vrai que la distinction n'est pas forcément évidente à appréhender au premier abord et la syntaxe RDF/XML n'arrange pas les choses. On dit d'un flux XML qu'il est bien-formé s'il respecte la logique d'imbrication des balises (à la « poupée russe »), qu'il possède un élément racine et quelques règles primitives de XML. Reprenons l'exemple donnée par Manue, soit la phrase : « Socrate est un chat ». <html> <head> <title>Description de Socrate</title> </head> <body> <p>Socrate est un chat</p> </body></html>

Heritrix - Heritrix - IA Webteam Confluence This is the public wiki for the Heritrix archival crawler project. Heritrix is the Internet Archive's open-source, extensible, web-scale, archival-quality web crawler project. Heritrix (sometimes spelled heretrix, or misspelled or mis-said as heratrix/heritix/ heretix/heratix) is an archaic word for heiress (woman who inherits). Since our crawler seeks to collect and preserve the digital artifacts of our culture for the benefit of future researchers and generations, this name seemed apt. All topical contributions to this wiki (corrections, proposals for new features, new FAQ items, etc.) are welcome! Heritrix is designed to respect the robots.txt exclusion directives and META robots tags, and collect material at a measured, adaptive pace unlikely to disrupt normal website activity. If you notice our crawler behaving poorly – The Internet Archive uses archive.org_bot as User Agent when crawling – please send us email at archive-crawler-agent@lists.sourceforge.net. Heritrix 3.2.0 (Jan 2014)

Linked Science Vocabulary Specification Back to LinkedScience.org 29 November 2011 This version: Latest version: Previous version: Revision: Revision: 0.91 Authors: Alkyoni Baglatzi (Institute for Geoinformatics, University of Muenster, Germany) Tomi Kauppinen (Institute for Geoinformatics, University of Muenster, Germany) Carsten Keßler (Institute for Geoinformatics, University of Muenster, Germany) Contributors: See acknowledgements. Copyright © 2011 - 2011 Alkyoni Baglatzi and Tomi Kauppinen, Institute for Geoinformatics, University of Muenster, Germany. This work is licensed under a Creative Commons License. Linked Science Vocabulary Specification relies on W3C's RDF technology, an open Web standard that can be freely used by anyone. This visual layout and structure of the specification was adapted from the Open Provenance Model Vocabulary edited by Jun Zhao, SIOC Core Ontology Specification edited by Uldis Bojars and John G.

RDF Schema 1.1 Abstract RDF Schema provides a data-modelling vocabulary for RDF data. RDF Schema is an extension of the basic RDF vocabulary. Status of This Document This section describes the status of this document at the time of its publication. Other documents may supersede this document. This document is an edited version of the 2004 RDF Schema Recommendation. This document was published by the RDF Working Group as a Recommendation. This document has been reviewed by W3C Members, by software developers, and by other W3C groups and interested parties, and is endorsed by the Director as a W3C Recommendation. This document was produced by a group operating under the 5 February 2004 W3C Patent Policy. Table of Contents 1. RDF Schema provides a data-modelling vocabulary for RDF data. This document is intended to provide a clear specification of RDF Schema to those who find the formal semantics specification [RDF11-MT] daunting. RDF Schema is a semantic extension of RDF. 2. 2.1 rdfs:Resource 2.2 rdfs:Class

decision-ontology - An ontology for representing decisions and decision-making The purpose of Decision Ontology (DO) is to provide a basis for representing, modeling and analyzing decision and decision-making. You can browse the ontology here. Visit the wiki section for more information. If you have any questions or comments or need help in using this ontology, send an email to: piotrnowara(at)gmail.com April 2012 - improved annotations and new 'How to' wiki page. October 2011 - new version of Decision Ontology is available - please check the repository and this wiki page. Representing decisions & decision-making Decision ontology can be used for archiving information related to the decisions and their context. Decision Ontology can be used for storing and analyzing decision patterns that is the knowledge associated with certain types of decision, where every aspect could be analyzed hierarchically. Examples: Some of the questions that can be answered using DO: What problem/question initiated the decision-making process? This project is open for collaboration.

Introduction à RDFa Résumé Le Web actuel est conçu essentiellement pour une consommation humaine. Et même lorsque des données interprétables font leur apparition sur le Web, elles sont typiquement distribuées dans un fichier séparé, avec un format séparé et une correspondance très limitée entre les versions homme et machine. En conséquence, les navigateurs Web ne peuvent fournir qu'une aide minimale aux humains pour l'analyse et le traitement des données web : les navigateurs voient seulement l'information de présentation. Nous introduisons RDFa, qui fournit un ensemble d'attributs XHTML pour prolonger les données visuelles par des indications intelligibles aux machines (machine-readable). Ce document n'est qu'une introduction à RDFa. Statut de ce document Cette section décrit le statut de ce document au moment de sa publication. Ce document est une note de groupe de travail produite conjointement par le groupe de travail Semantic Web Deployment [SWD-WG] et le groupe de travail XHTML 2 [XHTML2-WG] du W3C.

Linked Data | Linked Data - Connect Distributed Data across the Web Welcome to the Bibliographic Ontology Website | The Bibliographic Ontology RDF Schema Un article de Wikipédia, l'encyclopédie libre. La première version de RDFS a été proposée en mars 1999, et la recommandation finale publiée par le W3C en février 2004. Les composants principaux de RDFS sont intégrés dans un langage d'ontologie plus expressif, OWL. Principales caractéristiques de RDFS[modifier | modifier le code] Classes et sous-classes[modifier | modifier le code] Un exemple simple de rdfs:Class est foaf:Person dans le vocabulaire FOAF. ex:Jean rdf:type foaf:Person La définition de rdfs:Class est récursive. rdfs:Class est la classe de toutes les classes. rdfs:subClassOf permet de définir des hiérarchies de classes. Par exemple, 'Toute personne est un Agent': foaf:Person rdfs:subClassOf foaf:Agent Propriétés[modifier | modifier le code] RDFS précise la notion de propriété définie par RDF en permettant de donner un type ou une classe au sujet et à l'objet des triplets. rdfs:domain définit la classe des sujets liée à une propriété. ex:travailledans rdfs:domain foaf:Person

What is PredictionIO? Why do developers like it? Developers can get started quickly by downloading one of the many engine template available on PredictionIO template gallery. They can further customize each component of an engine for any specific business logics they have in mind. The DASE architecture offers separation-of-concerns, making it easier for them to re-use and maintain the code. With Event Server and SDKs, developers can integrate PredictionIO easily with applications and platforms of any programming language. PredictionIO manages the deployment of engines with scalability in mind. PredictionIO helps developers build and deploy production-grade predictive engines, faster. Why do data scientists like it? Data scientists use PredictionIO to evaluate models and keep track of parameter adjustment history. PredictionIO helps data scientists evaluate and tune multiple models in parallel effectively and systematically. Use Cases See some examples of what can be built with PredictionIO

Report on Persistent Identifiers [CERL] Hans-Werner Hilse and Jochen Kothe, Implementing Persistent Identifiers: Overview of concepts, guidelines and recommendations. London / Amsterdam: Consortium of European Libraries and European Commission on Preservation and Access, 2006. ISBN 90-6984-508-3. Download PDF version (persistent identifier): Traditionally, references to web content have been made by using URL hyperlinks. The report explains the principle of persistent identifiers and helps institutions decide which scheme would best fit their needs. The report was written by the Research and Development Department of the Goettingen State and University Library (Niedersächsische Staats- und Universitätsbibliothek Göttingen) at the request of the Advisory Task Group (ATG) of the Consortium of European Research Libraries.

RDF-Gravity Sunil Goyal, Rupert Westenthaler {sgoyal, rwestenthaler}@salzburgresearch.at Salzburg Research, Austria RDF Gravity is a tool for visualising RDF/OWL Graphs/ ontologies. Its main features are: Graph VisualizationGlobal and Local Filters (enabling specific views on a graph) Full text SearchGenerating views from RDQL QueriesVisualising multiple RDF files RDF Gravity is implemented by using the JUNG Graph API and Jena semantic web toolkit. Figure 1: Screenshot of RDF-Gravity, showing a part of Wine Ontology 1 Graph Visualisation RDF Gravity defines a visualization package on top of the JUNG Graph API. Configurable renderers for edges and nodes of a graph, including different node shapes and edge decorations etc.A Renderer Factory allowing the configuration of the above node and edge renderers based on the type of an edge or node. For graph layout, it uses the layout algorithms directly supported by the Jung API. 2 Global & Local Filters 3 Full Text Search 4 Visualising Multiple RDF Files

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