Difference between revisions of "RDFSharp"

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** Create and execute <u>SPARQL queries</u> on graphs, stores and federations to fluently query RDF data;
 
** Create and execute <u>SPARQL queries</u> on graphs, stores and federations to fluently query RDF data;
  
* <b>SEMANTICS (<i>under design</i>)</b>
+
* <b>SEMANTICS (<i>under development</i>)</b>
 
** Create and validate <u>RDF ontologies</u> (classes, properties, constraints, facts, ...);
 
** Create and validate <u>RDF ontologies</u> (classes, properties, constraints, facts, ...);
 
** Create and execute <u>RDF reasoners</u> on them, materializing inferred RDF data;
 
** Create and execute <u>RDF reasoners</u> on them, materializing inferred RDF data;

Revision as of 13:38, 7 May 2014

RDFSharp

Name of the tool: RDFSharp
Home page: http://rdfsharp.codeplex.com
Date of latest release:
Programming language(s) that can be used with the tool: .Net, C-sharp
Relevant semantic web technologies: RDF, SPARQL, RDFS
Categories: API, Programming Environment
See also:
Public mailing list:
Preferred project URI:
DOAP reference:
Company or institution:

(Tool description last modified on 2014-05-7.)

Description

RDFSharp is a lightweight C# framework designed to ease the creation of .NET applications based on the RDF model, representing a straightforward didactic solution for start playing with RDF and Semantic Web concepts. With RDFSharp it is possible to draft .NET applications capable of modeling, storing and querying RDF data.

RDFSharp has a modular API made up of four layers:

  • MODEL
    • Create and manage RDF models (resources, literals, triples, graphs, namespaces, datatypes, ...);
    • Exchange them using standard RDF formats (NTriples, TriX, Turtle, RDF/XML);
  • STORE
    • Create and manage RDF stores backing on memory or on different SQL engines (Firebird, MySQL, SQLite, SQL Server);
    • Create and manage RDF federations as virtual stores giving integrated query access to multiple stores;
  • QUERY
    • Create and execute SPARQL queries on graphs, stores and federations to fluently query RDF data;
  • SEMANTICS (under development)
    • Create and validate RDF ontologies (classes, properties, constraints, facts, ...);
    • Create and execute RDF reasoners on them, materializing inferred RDF data;