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Index. Projet. PostGIS on Amazon RDS: A Spatial Database in the Cloud. An announcement at the AWS:Invent 2013 conference that got me excited was the new support for PostgreSQL on Amazon Web Service’s (AWS) Relational Database Service (RDS). I crossed my fingers as I read the announcement, hoping that PostGIS was part of this. “No Way!” I thought after reading that PostGIS was indeed! I knew I had to try it out. Image via Techcrunch article: Running PostGIS on RDS I fired up an RDS instance of PostgreSQL to see for myself.

I used FME to read and write data to this PostGIS database as it would any other PostGIS. FME and PostGIS in the Cloud The implications of this are huge, especially when I think about our new FME Cloud iPaaS service. Doing this is a game changer. With PostGIS now supported by RDS, anyone can easily deploy a class-leading fault-tolerant database that spans multiple data centers (or AZ in Amazon speak) in minutes. FME Cloud. IT (513) What is Linked Data? Croiser des statistiques : l’enjeu des URI. Voilà un cas pratique qui vient de tomber pour illustrer une utilisation "simple" (oserai-je "intuitive" ?) Des URI. L’enjeu Il y a quelques jours, Symac a initié sur Bibliopedia une page Services numériques en BU, afin de pouvoir décrire et comparer les "services numériques" (au sens décrit dans un précédent billet, c’est-à-dire avec toute la diversité des tâches qui vont ou non rentrer dans cette appellation) entre eux.

Si ce genre de tableau est intéressant, il est à mon sens forcément insuffisant : savoir qu’il y a 3 ou 10 personnes dans un tel service n’est vraiment utile que si ça peut devenir un outil d’aide à la décision, par exemple dans le cadre d’une réflexion sur une réorganisation interne. Mais pour comparer 2 SCD comptant, l’un 3 personnes et l’autre 10 dans son "service informatique", il faut par exemple savoir Certes, on pourrait reproduire ces informations, tirées de l’ESGBU (ou d’ailleurs), dans le tableau sur Bibliopedia.

Mise en application Identifiant PAPESR mais. Rdf. RDFa. Rdfonthego - RDF store and query processor. RDF On The Go is the project to build a persistent RDF store and query processor on Android phone. For storage of the data, RDF on The Go uses a lightweight version of the Berkeley DB that is suitable for mobile devices, which provides a B-Tree implementation for accessing the RDF graphs. For each RDF node, the system employs dictionary encoding where node values are mapped to integer identi ers. This reduces the space required to store each RDF node, since the encoded version of the nodes are considerably smaller than the original ones. Moreover, dictionary encoding also allows faster processing, since integer comparisons are cheaper. Fast lookups are achieved in a two-step approach: fi rst, each triple node is stored in multiple ways with different orderings of the triple elements, similar to Hẽxastore.

Then indexes are built for every ordering of the triple pattern, as proposed in. Tutorial. What is RDF and what is it good for? How RDF Databases Differ from Other NoSQL Solutions - The Datagraph Blog. This started out as an answer at Semantic Overflow on how RDF database systems differ from other currently available NoSQL solutions. I've here expanded the answer somewhat and added some general-audience context.

RDF database systems are the only standardized NoSQL solutions available at the moment, being built on a simple, uniform data model and a powerful, declarative query language. These systems offer data portability and toolchain interoperability among the dozens of competing implementations that are available at present, avoiding any need to bet the farm on a particular product or vendor. In case you're not familiar with the term, NoSQL ("Not only SQL") is a loosely-defined umbrella moniker for describing the new generation of non-relational database systems that have sprung up in the last several years.

These systems tend to be inherently distributed, schema-less, and horizontally scalable. Present-day NoSQL solutions can be broadly categorized into four groups: RDF Web Applications Working Group. Current and Upcoming Events Teleconferences: The first Thursday of each month at 10am US Eastern time. An agenda is sent to rdfa-wg 24 hours in advance; minutes follow within a day or two. Will be monitoring comments on any specification or test cases W3C Standards and Notes HTML+RDFa 1.1 (REC) This specification defines rules and guidelines for adapting the RDFa Core 1.1 and RDFa Lite 1.1 specifications for use in HTML5 and XHTML5. Inputs RDFa Core 1.1, W3C Recommendation, June 7, 2012, Ben Adida, Mark Birbeck, Shane McCarron, Ivan Herman,, , eds. See the Working Group Wiki for further input documents, drafts, etc.

Schedule of Deliverables HTML +RDFa 1.1, Recommendation: This document will specify the behaviour of HTML5 and XHTML5 as host languages to RDFa 1.1 Core. The group may also issue an Edited Recommendation for RDFa 1.1 Core, RDFa Lite 1.1 and XHTML+RDFa 1.1, folding in the possible editorial errata. Milestones Timeline View Summary Patent Policy History.

RDF and Mind Maps. Kerstin Forsberg has written an article about mind maps and how the concept of mapping the mind calls for RDF triples and formal models. She writes, “When I see these mind maps I see graphs just begging for RDF triples (subject, predicate, object)… An interesting exercise would be to have the Parkinson’s disease example completed in the concept mapping tool (CMAP) the whole way down to SDTM. And export the mind maps using as RDF triples.” She goes on, “When I these mind maps I can also see how easy it is to start drawing such diagrams and exporting them as representations of generic mind maps. However, to fulfill the ultimate goal to have them ’captured in a way that these can be used both for human understanding and for computer interpretation’ the ‘mind maps’ need underlying formal models of the clinical and biomedical reality.

Therefore, I see an interesting connection between the high level maps for disease and clinical processes to the Ontology for General Medical Science (OGMS). Introduction to: RDF vs XML. There has always been a misconception between the relationship of RDF and XML. The main difference: XML is a syntax while RDF is a data model. RDF has several syntaxes (Turtle, N3, etc) and XML is one of those (known as RDF/XML). Actually, RDF/XML is the only W3C standard syntax for RDF (Currently, there is Last Call on Turtle, a new W3C standard syntax for RDF).

Therefore, comparing XML and RDF is like comparing apples with oranges. What can be compared is their data models. Comparing RDF with XML Joshua Tauberer has an excellent comparison between RDF and XML, which I recommend. Flexibility of the Data Model There are different ways of representing data in XML. <product> <title>iPhone</title> <price>$200</price> </product> Another valid XML could be: <product title=”iPhone”> <price>$200</price> </product> Modeling this same data in RDF would only have one way of representing it: ex:product1 rdf:type ex:Product . ex:product1 ex:title “iPhone” . ex:product1 ex:price “200″ . Summary. RDF triple stores — an overview | Larsblog. There's a huge range of triple stores out there, and it's not trivial to find the one most suited for your exact needs. I reviewed all those I could find earlier this year for a project, and here is the result. I've evaluated the stores against the requirements that mattered for that particular project.

I haven't summarized the scores, as everyone's weights for these requirements will be different. By a triple store I mean a tool that has some form of persistent storage of RDF data and lets you run SPARQL queries against that data. The SPARQL support can either be built-in as part of the main tool, or an add-on installed separately. I've deliberately left out rows for whether these tools support things like R2RML, query federation, data binding, SDshare, and so on, even though many of them do. I've also deliberately left out cloud-only offerings, as I feel these are a different type of product from the databases you can install and maintain locally. How RDF Databases Differ from Other NoSQL Solutions - The Datagraph Blog.

Pour aller plus loin avec RDFa. Je répète à longueur de temps que structurer un contenu en XML, et a fortiori en HTML, ne constitue pas une sémantisation, mais permet d'indiquer le rôle joué par la portion d'information dans le contexte d'un document. Les normes du Web sémantique ont à l'inverse vocation à aider à la sémantisation du contenu. Mais, à force de le répéter sans rien montrer de probant, vous allez finir par croire que c'est une chimère.

Soyons clairs, nous sommes encore loin du compte, mais nous avons fait des avancées, exemple avec RDFa. RDFa fait déjà énormément parler de lui, comme le prouvera ma prochaine pelote. En indiquant la propriété Dublin Core "creator", j'ai bien précisé que la chaîne de caractères "Gautier Poupeau" est le créateur du document.

<span rel="dc:creator" href=" Gautier Poupeau </span> Maintenant que je vous ai brossé à grands traits les RDFa, passons au vif du sujet : "et si on sémantisait un peu le Web". Quelles utilités ? III-A. Transforming Relational Data to RDF – R2RML Becomes Official W3C Recommendation. Today, the World Wide Web Consortium announced that R2RML has achieved Recommendation status. As stated on the W3C website, R2RML is “a language for expressing customized mappings from relational databases to RDF datasets. Such mappings provide the ability to view existing relational data in the RDF data model, expressed in a structure and target vocabulary of the mapping author’s choice.” In the life cycle of W3C standards creation, today’s announcement means that the specifications have gone through extensive community review and revision and that R2RML is now considered stable enough for wide-spread distribution in commodity software.

Richard Cyganiak, one of the Recommendation’s editors, explained why R2RML is so important. “In the early days of the Semantic Web effort, we’ve tried to convert the whole world to RDF and OWL. “That’s why technologies that map existing data formats to RDF are so important,” he continued. RGI_Version1 0.pdf. RDF: The Basics. A new article by Ric Roberts offers an introductory-level explanation of RDF for newcomers to the Semantic Technology space. Roberts begins, “Linked Data is based around describing real world things using RDF. A lot of articles about Linked Data assume you already know what RDF is all about: if you are coming to it for the first time, this article explains the basics.

RDF stands for Resource Description Framework. It’s a W3C standard for modeling information.” He continues, “RDF allows you to define statements about things (or resources), in the form of subject-predicate-object expressions (known as RDF-triples due to the 3 constituent parts). This might sound very technical, but the meanings of subject, predicate, and object are essentially the same as in English grammar. Read more here. Image: Courtesy Flickr/ Beercha. Publier des stats en RDF (1) : ébauche et errances. Comme annoncer dans un précédent billet, je compte exploiter le cas des données PAPESR (statistiques sur les Universités) pour voir comment publier des données statistiques en RDF.

Pour commencer, je suis passé par le SCOVO (mentionné comme deprecated) pour arriver au RDF Data Cube Vocabulary. J’y reviendrai, mais d’emblée j’ai dans l’idée que le graphe produit pourrait ressembler vaguement à ça : Explications et remarques En rouge, le "noeud" Université, qui sert de point de départ. Ne prenez pas le schéma pour argent comptant : comme je le disais, je tâtonne et je n’ai pas lu le quart de ce que j’aurais dû lire pour me lancer là-dedans. Ce qui me gêne, après avoir lu le début du RDF Data Cube Vocabulary (mais pas encore terminé, ni encore moins assimilé), c’est qu’avec le graphe ci-dessus je restitue surtout l’arborescence d’un fichier XML, qui suit en cascade le chemin : Universités françaises > Université N > Nb d’étudiants > XXX.

Donc si ça se trouve, j’ai tout fait à l’envers.