Google Image Swirl organizes image search results based on their visual and semantic similarities and presents them in an intuitive exploratory interface.

Martha asks a number of questions about RDF in the article. Even the title is a question: "Can Bibliographic data be Put Directly onto the Semantic Web?" (Answer: it already is ) Martha is conducting an admirable gedanken experiment about the future of cataloging, creating her own cataloging code and trying to mesh her ideas with concepts coming out of the semantic web community. The article's value is not only in her conclusions but in the questions that she raises. In its unfinished state, Martha's thinking is provocative and just begging for further discussion and development.

Finalement, nous avons discuté organisation et compétences (deux thèmes qui me tiennent fort à cœur ;-) car si nous voulons vraiment que le Linked Data ait un avenir dans les bibliothèques, il va falloir que différents niveaux d'acteurs s'y intéressent et s'y investissent. De ce point de vue, la désaffection de la profession pour les questions de métadonnées (yes, MARC c'est tellement has been) me paraît inquiétante.

Ce site constitue un prototype pour démontrer les possibilités de mashup avec les données du Linked Data et les technologies du Web sémantique.

This places everybody trying to make the web of data happening in danger of oper-promising and under-delivering, which is not a recipe for success: it’s a recipe for abuse, mistrust and anger… which ultimately leads to disaster and failure.

Link using our stable URL pattern for titles, issues, editions, and pages.

Linked Data views of information about titles, batches, issues, and pages in RDF/XML.

Yields each triple, or generate in-memory graph

Why is it good? Because we’ll learn a few tricks about how to do stuff with just JavaScript and no yucky backend stuff like PHP.

There are two advantages of using a resource here rather than a literal value:You can associate other metadata with the term. You can more accurately and easily associate multiple documents that use the same term.

VoCamp is a series of informal events where people can spend some dedicated time creating lightweight vocabularies/ontologies for the Semantic Web/Web of Data. The emphasis of the events is not on creating the perfect ontology in a particular domain, but on creating vocabs that are good enough for people to start using for publishing data on the Web. The intention is to follow a "paper first, laptops second" format, where the modelling is done initially on paper and only later committed to code. The VoCamp idea is influenced by BarCamp, although the emphasis is different. Whereas BarCamps are oriented to demos and presentations, VoCamps are oriented to hands-on technical work and practical outputs; any presentations and demos should be short, highly on-topic to the vocabulary development process, and limited in number, to leave plenty of time for hacking on new vocabularies.

Way back in 2006 I wrote a blog post concerning the modelling of time in RDF (see Refactoring Bio With Einstein Part 3: Temporal Invariants. That post also provoked some discussion in the blogosphere. Although I haven’t written anything on the subject for the past three years I haven’t stopped thinking about it. In fact I’ve been working quite hard on the problem, mainly by modelling real data, especially geographical information. This is the first of a series of blog posts describing my experiments. I’d like to thank Leigh Dodds and Jeni Tennison who gave me valuable feedback on an earlier version of this write-up.

Summary: As more data is being stored in RDF formats like RSS, a need has arisen for a simple way to locate specific information. SPARQL, a powerful new query language fills that space, making it easy to find the data you need in the RDF haystack. Take a tour of SPARQL's features and learn how to use SPARQL queries from your own Java™ applications with the Jena Semantic Web Toolkit.

The hyperdata Address Book project being developed here is meant to be the equivalent for foaf that BlogReaders are for RSS. It is a specialised Semantic Web browser that follows foaf documents around the web, building a distributed open social network. It is also a foaf editor, which you can use to publish your foaf files to an ftp/scp server.

Social OPAC application suite--an award-winning, open source social discovery platform for bibliographic data. The purpose of this site is to build a cohesive community of users and developers around the SOPAC project suite.

Mais en RDF, contrairement à XML, chaque triplet est indépendant et signifiant indépendamment de tout contexte, ce qui signifie que je peux tout à fait utiliser pour décrire la même ressource des propriétés du Dublin Core et d'autres propriétés, venant d'autres vocabulaires ou ontologies.

Stop Forcing Things Into Hierarchies

A skim-read introduction to linked data

The New York Times includes a large amount of topical metadata with each article it publishes. These daily dumps plot the relationships, and geographies, of each article and are archived as RDF, XHTML and SVG maps.

The point of this exercise was mainly to show how thinking of the New York Times Topics as a controlled vocabulary, that can be serialized as a file, and still present on the Web, could be useful.

Releasing the Times thesaurus is consistent with our TimesOpen strategy. We want to facilitate access to slices of our data for those who want to include Times content in their applications.

What makes Bintro special is its use of advanced semantic technology for the purpose of matchmaking. There are no multiple choice questions. There are no numbered scales. All you need to do is describe yourself and your needs and Bintro will take care of the rest. All the words and phrases you use are analyzed to an extremely high level on the basis of similarity and usage. This process is completed within seconds and matches are presented to you as they become available. After this, Bintro will continue to find more matches for you every minute of every day.

I have written a wrapper to expose openlibrary.org api data as RDF. It is written in Python and deployed on Google App Engine. It is only an illustration of Linked Data publication, and in order to get a first feedback, so do not rely on it in your application since the URL or the content will change in the future.

This document describes an ontology for publishing descriptions of historical events as Linked Data, and for mapping between other event-related vocabularies and ontologies.