Using Dublin Core - The Elements NOTE: This text was last revised in 2005. As of 2011, a completely revised User Guide is being developed at the wiki page DCMI's Glossary and FAQ are also under revision. This section lists each element by its full name and label. In the element descriptions below, a formal single-word label is specified to make the syntactic specification of elements simpler for encoding schemes. Some information may appear to belong in more than one metadata element. 4.1. Label: Title Element Description: The name given to the resource. Guidelines for creation of content: If in doubt about what constitutes the title, repeat the Title element and include the variants in second and subsequent Title iterations. Examples: Title="A Pilot's Guide to Aircraft Insurance" Title="The Sound of Music" Title="Green on Greens" Title="AOPA's Tips on Buying Used Aircraft" 4.2. Label: Subject and Keywords Element Description: The topic of the content of the resource. 4.3.
Linked Data | Linked Data - Connect Distributed Data across the Data Incubator Open Data An introductory overview of Linked Open Data in the context of cultural institutions. Clear labeling of the licensing terms is a key component of Open data, and icons like the one pictured here are being used for that purpose. Overview[edit] The concept of open data is not new; but a formalized definition is relatively new—the primary such formalization being that in the Open Definition which can be summarized in the statement that "A piece of data is open if anyone is free to use, reuse, and redistribute it — subject only, at most, to the requirement to attribute and/or share-alike Open data is often focused on non-textual material[citation needed] such as maps, genomes, connectomes, chemical compounds, mathematical and scientific formulae, medical data and practice, bioscience and biodiversity. A typical depiction of the need for open data: Creators of data often do not consider the need to state the conditions of ownership, licensing and re-use. I want my data back. Closed data[edit]
Primer - Getting into the semantic web and RDF using N3 [translations into other languages ] The world of the semantic web, as based on RDF, is really simple at the base. This article shows you how to get started. It uses a simplified teaching language -- Notation 3 or N3 -- which is basically equivalent to RDF in its XML syntax, but easier to scribble when getting started. Subject, verb and object In RDF, information is simply a collection of statements, each with a subject, verb and object - and nothing else. <#pat><#knows><#jo> . Everything, be it subject, verb, or object, is identified with a Uniform Resource Identifier. There is one exception: the object (only) can be a literal, such as a string or integer: <#pat><#knows><#jo> . The verb "knows" is in RDF called a "property" and thought of as a noun expressing a relation between the two. <#pat><#child><#al> . alternatively, to make it more readable, as either <#pat> has <#child><#al> . or <#al> is <#child> of <#pat> . <#pat><#child><#al>, <#chaz>, <#mo> ; <#age> 24 ; <#eyecolor> "blue" . . . More
Web sémantique : quand le Web devient données : Introduction Quand la donnée prend le dessus. C’est ainsi que pourrait être, très vulgairement, résumé le Web sémantique. Un vaste projet qui a éclaté aux yeux de tous suite à l‘intervention de Tim Berners-Lee, patron du W3C - et également père du Web -, le consortium en charge de définir les standards du Web. “J’ai un double rêve pour le Web. Une vision un peu magique d’un environnement connecté où seul le sens de l’information, de la donnée serait pris en compte pour livrer à l’internaute une information riche, contextualisée et fortement qualifiée. Les activités liées au Web sémantique existent depuis 1998 au sein du W3C, et ont débouché depuis sur l’éclosion d’une série de technologies qui forment l’ossature de l’ensemble. Ce dossier vise à décrypter les mécanismes du Web sémantique, en tentant de livrer une définition aussi claire que possible, de faire un état des lieux des technologies qui orchestrent ce beau concept.
50 Great Examples of Data Visualization Wrapping your brain around data online can be challenging, especially when dealing with huge volumes of information. And trying to find related content can also be difficult, depending on what data you’re looking for. But data visualizations can make all of that much easier, allowing you to see the concepts that you’re learning about in a more interesting, and often more useful manner. Below are 50 of the best data visualizations and tools for creating your own visualizations out there, covering everything from Digg activity to network connectivity to what’s currently happening on Twitter. Music, Movies and Other Media Narratives 2.0 visualizes music. Liveplasma is a music and movie visualization app that aims to help you discover other musicians or movies you might enjoy. Tuneglue is another music visualization service. MusicMap is similar to TuneGlue in its interface, but seems slightly more intuitive. Digg, Twitter, Delicious, and Flickr Internet Visualizations
LinkedData - ESW Wiki LinkedData is to spreadsheets and databases what the Web of hypertext documents is to word processor files. Use URIs as names for things Use HTTP URIs so that people can look up those names. When someone looks up a URI, provide useful information. Include links to other URIs. so that they can discover more things groupage cargo service. Linked Data Presentations: Writings: Workshop Series about Linked Data at the WWW conferences Other Workshops about Linked Data 1st International Workshop on Consuming Linked Data (COLD 2010) at ISWC 2010 Community: Examples of Linked Data: See DataSets Client side tools: Server side tools: dbview.py by DanConnolly, Rob Crowell and TimBL Virtuoso - "Sponger" component of Virtuoso's SPARQL Engine, RDF Views of SQL, and the HTTP engine's Linked Data Deployment features D2R Server P2R - expose Prolog knowledge base as linked data (when bundled with UriSpace) SPARQL2XQuery - Bridging the Gab between the XML and the Semantic Web Worlds. Live Demos: Meetups:
The Linking Open Data cloud diagram Semantic Web Crawling: A Sitemap Extention Abstract This document describes an extension to the Sitemap protocol targeted at the efficient discovery and use of RDF data. The extension allows Data publishers to state where documents containing RDF data are located, and to advertise alternative means to access it, such as data dumps and SPARQL endpoints. Table of Contents 1. Data on the Semantic Web can be made available and consumed in many ways. For example, a Semantic Web crawler that wants to index an entire database might prefer to download the dump, instead of retrieving the data piecemeal by fetching individual URIs. In either case, clients can only make smart decisions if the publisher has advertised the fact that the same data is available through different access method. Publishers should be aware that a sitemap does not enforce any client behaviour. 2. A dataset is a set of RDF triples that are managed, stored, or published together. Exceptions to this rule should be limited to 3. An <sc:dataset> tag declares a dataset.
Flare | Data Visualization for the 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. With linked data, when you have some of it, you can find other, related, data. Like the web of hypertext, the web of data is constructed with documents on the web. However, unlike the web of hypertext, where links are relationships anchors in hypertext documents written in HTML, for data they links between arbitrary things described by RDF,. 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 basic format here for RDF/XML, with its popular alternative serialization N3 (or Turtle). Basic web look-up or in RDF/XML