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ReVerb - Open Information Extraction Software. ConceptNet 5. Guides. RDF 101. Introduction RDF (Resource Description Framework) is one of the three foundational Semantic Web technologies, the other two being SPARQL and OWL. In particular, RDF is the data model of the Semantic Web. That means that all data in Semantic Web technologies is represented as RDF. If you store Semantic Web data, it's in RDF. If you query Semantic Web data (typically using SPARQL), it's RDF data. If you send Semantic Web data to your friend, it's RDF. In this lesson we will introduce RDF. Objectives In this lesson you will learn: What RDF is and how it fundamentally differs from XML and relational databases What is meant by a "graph data model" How RDF is typically represented visually The importance of the URI, and the significance (or lack thereof) of identity "universality" Prerequisites Introduction to the Semantic Web Today's Lesson RDF is the foundation of the Semantic Web and what provides its innate flexibility.
RDF is not like the tabular data model of relational databases. RDF Graphs. FOAF Vocabulary Specification. Classes Class: foaf:Agent Agent - An agent (eg. person, group, software or physical artifact). The Agent class is the class of agents; things that do stuff. A well known sub-class is Person, representing people.
The Agent class is useful in a few places in FOAF where Person would have been overly specific. [#] [back to top] Class: foaf:Document Document - A document. The Document class represents those things which are, broadly conceived, 'documents'. The Image class is a sub-class of Document, since all images are documents. We do not (currently) distinguish precisely between physical and electronic documents, or between copies of a work and the abstraction those copies embody. [#] [back to top] Class: foaf:Group Group - A class of Agents. The Group class represents a collection of individual agents (and may itself play the role of a Agent, ie. something that can perform actions). The markup (shown below) for defining a group is both complex and powerful. Here is an example. <! [#] [back to top] Tdwg-rdf - TDWG RDF/OWL Task Group. Background The RDF/OWL Best Practices Task Group is part of Biodiversity Information Standards (TDWG; ).
Its purpose is to adapt TDWG vocabularies for use as RDF classes and properties and to integrate those resources with other well-known vocabularies and ontologies outside TDWG for use in describing biodiversity resources. Group discussions are conducted via an email list hosted and archived at . Please visit that site to request an invitation to be added to the list. The issues tracker is set up to handle specific best-practices recommendations, missing terms, etc. Our charter was approved by the TDWG executive at the 2011 meeting in New Orleans. RDF Sandboxes/Development platforms The sandboxes are places to experiment with RDF. Two triple stores available here, one based on 4store, one based on AllegroGraph .
Beginner's Guide to RDF Click here to go to the Introduction of the Guide. Dave Beckett's Resource Description Framework (RDF) Resource Guide.
W3C Resources. TaskForces/CommunityProjects/LinkingOpenData/DataSets/Statistics - W3C Wiki. SWEO Community Project: Linking Open Data on the Semantic Web This page collects statistics on Data sets that are available as Linked Data. Please note: This page is outdated For keeping the LOD cloud diagram up to date, the Linking Open Data community effort has started to collect meta-information about Linked datasets on CKAN, a registry of open data and content packages provided by the Open Knowledge Foundation. The meta-information from CKAN (and not from this page) is used to draw the LOD cloud diagram and to maintain the statistics about the size of the Web of Linked Data on the EWS LOD frontpage. The list of Linked Dataset for which we have already collected meta-information on CKAN is found here: LOD dataset list Basic statistics about these datasets are provided at: LOD basic statistics A guide on how to describe your dataset on CKAN is found here: LOD CKAN Guidlines Historic Version of this page.
RDF - Semantic Web Standards. Overview RDF is a standard model for data interchange on the Web. RDF has features that facilitate data merging even if the underlying schemas differ, and it specifically supports the evolution of schemas over time without requiring all the data consumers to be changed. RDF extends the linking structure of the Web to use URIs to name the relationship between things as well as the two ends of the link (this is usually referred to as a “triple”). Using this simple model, it allows structured and semi-structured data to be mixed, exposed, and shared across different applications. This linking structure forms a directed, labeled graph, where the edges represent the named link between two resources, represented by the graph nodes. This graph view is the easiest possible mental model for RDF and is often used in easy-to-understand visual explanations. Recommended Reading The RDF 1.1 specification consists of a suite of W3C Recommendations and Working Group Notes, published in 2014.
Databases. SemanticWebTools - W3C Wiki. From W3C Wiki REDIRECT New SemanticWiki Tools Page As of 12:50, 14 January 2010, this page is no longer maintained and should not be changed. The content has been transferred to . (Changes made here after the above date may not be reflected on the new page !) Please consult and possibly modify that page .
Table of Contents: This page contains the information on RDF and OWL tools that used to be listed on the home pages of the RDF and OWL Working Groups at W3C. This Wiki page is only for programming and development tools. There are other pages on tool collection, largely overlapping with this, but possibly with a different granularity or emphasis. There are also separate pages maintained on this Wiki for: SPARQL implementations , set up by the SPARQL Working Group (although most of the information is present on this page, too) SPARQL "endpoints" , examples of using SPARQL in exposing various data. Adobe's XMP Altova's SemanticWorks Amilcare Arity's LexiLink Rej. Jena Relational Database backend.
This document provides some details on the Jena2 database schema and the encoding used to store URIs and literal values. Overview - Denormalized Triple Store A widely-used scheme for storing RDF statements in a relational database is the triple store . In this approach, each RDF statement is streod as a single row in a three column 'statement' table. Typically, a fourth column is added to indicate if the object is a literal or a URI. A common variation of this scheme which uses much less storage space is the normalized triple store approach. This scheme uses a statement table plus a literals table and a resources table. The literals table stores the literals for all statements and the resources table stores all the resources from all the statements. Jena2 stores RDF statements using a denormalized triple store approach which is a hybrid of the standard triple store and the normalized triple store. Statement Tables Asserted Statement Table (Jena_G i T j _Stmt) System Tables Primary Key: Id.
Apache Jena - Apache Jena. LargeTripleStores - W3C Wiki. This page is for references to signed quotes of deployments of large triples stores rather than predictions of what some software might scale to. Table of Contents: AllegroGraph (1+Trillion) Franz announced at the June 2011 Semtech conference a load and query of 310 Billion triples as part of a joint project with Intel. In August 2011, with the help of Stillwater SC and Intel we achieved the industry's first load and query of 1 Trillion RDF Triples.
The driving force has been Amdocs and their AIDA platform. We currently load LUBM 8000 in just over 36 minutes. Franz is in late-stage development on a clustered version of AllegroGraph that will push storage into trillions of triples. Note 1: AllegroGraph provides dynamic reasoning and DOES NOT require materialization. Stardog (50B) Stardog is a pure Java RDF database which supports all of the OWL2 profiles using a dynamic (backward-chaining) approach. OpenLink Virtuoso v6.1 - 15.4B+ explicit; uncounted virtual/inferred Benchmarks data sources. Triplestore. Much like a relational database, one stores information in a triplestore and retrieves it via a query language. Unlike a relational database, a triplestore is optimized for the storage and retrieval of triples. In addition to queries, triples can usually be imported/exported using Resource Description Framework (RDF) and other formats.
Some triplestores can store billions of triples.[2] Implementation[edit] Some triplestores have been built as database engines from scratch, while others have been built on top of existing commercial relational database engines (i.e. List of implementations[edit] Technical overview[edit] The following table is an overview of available triplestores, their technical implementation, support for the SPARQL World Wide Web Consortium (W3C) recommendations, and available application programming interfaces (API). See also[edit] Freebase uses a triplestore called graphd[citation needed]Named graph a.k.a. References[edit] External links[edit] Storing RDF in a relational database. CREATE TABLE triples ( model bigint(20) DEFAULT '0' NOT NULL, subject bigint(20) DEFAULT '0' NOT NULL, predicate bigint(20) DEFAULT '0' NOT NULL, object bigint(20) DEFAULT '0' NOT NULL, objtype tinyint(3) unsigned DEFAULT '0' NOT NULL, KEY idx_subject_predicate (subject,predicate), KEY idx_model (model), KEY idx_object_predicate (object,predicate)); CREATE TABLE resources ( hash bigint(20) DEFAULT '0' NOT NULL, ns bigint(20) DEFAULT '0' NOT NULL, name varchar(254) DEFAULT '' NOT NULL, PRIMARY KEY (hash)); CREATE TABLE namespaces ( hash bigint(20) DEFAULT '0' NOT NULL, value varchar(254) DEFAULT '' NOT NULL, PRIMARY KEY (hash)); CREATE TABLE literals ( hash bigint(20) DEFAULT '0' NOT NULL, value longtext NOT NULL, PRIMARY KEY (hash)); CREATE TABLE models ( id bigint(20) DEFAULT '0' NOT NULL, uri varchar(254) DEFAULT '' NOT NULL, size int(11), PRIMARY KEY (id));
Project Open Data. List of decades. List of centuries. List of centuries From Wikipedia, the free encyclopedia Jump to: navigation, search The pages listed below contain information about trends and events in particular centuries and millenniums. Other time periods[edit] Past[edit] Future[edit] See also[edit] Content listings Lists Indices Retrieved from " Categories: Navigation menu Personal tools Namespaces Variants Views Actions Navigation Interaction Tools Print/export Languages This page was last modified on 4 February 2014 at 18:09.