The World Wide Web has set up a global information space such of consisting of linked documents. As the Web becomes more intertwined with our daily lives, there is an increasing desire for immediate access to raw data not being available on the Web or represent in hypertext documents. Linked Data offers a new publishing paradigm, which relates to data and not to documents. So the data can be a priority citizen of the Web, with the extension of the Web with a global data space based on open criteria (the Web of Data).
Linked Data also offers a method to simplify the re-usability, inter-linking, complementarity, and sharing data on the Web. Ontologies (data model of Linked Data) are promoted to be re-used to raise the value of Linked Data. A large amount of data published on the Semantic Web and a number of ontology repositories have been created and made available online. The growth of ontologies occurs functioning problems because there are dependencies which means an ontology may reuse and expand other ontologies, this reuse or editing in an ontology may impact the ontologies that depend on it. Therefore, it will hamper their efficient re-usability.
In this thesis, I present an academic and technical introduction to Linked Open Data (LOD) as a methodology for improving data description explicitly to simplify re-use. Starting by specifying the basic concepts and definitions such as RDF, Linked Data, Linked Open Data, Semantic Web, and SPARQL. I also describe the basic principles of Linked Data, the best practices and tools which are available for converting and creating LOD from Open Data; selecting URIs and vocabularies to specify and characterized resources; determine the type of data to return in a description of a resource on the Web; techniques for linking of data sets. I will also present the environment and suitable demonstration use-cases what I designed and created for implying the basic concepts and problems.