Linked Data is one of the core concepts and pillars of the Semantic Web, also known as the Web of Data. The Semantic Web is all about making links between datasets understandable not only to humans but also to machines, and Linked Data provides the best practices for making those links. Linked Data is a set of design principles for sharing machine-readable interlinked data on the Web.
The more things, concepts, objects, persons, locations are connected together, the more powerful the Web of Data is. However, in order to link, merge and integrate huge sets of data from disparate raw sources, the Linked Data movement needs basic guidelines to stick to.
The inventor of the World Wide Web and the creator and advocate of the Semantic Web and Linked Data, Sir Tim Berners-Lee, laid down the four design principles of Linked Data as early as in 2006.
The Uniform Resource Identifier (URI) is a single global identification, a kind of unique ID, for all things linked, so that we can distinguish between those things, integrate them without confusion, or know that one thing from one dataset is the same as another in a different dataset because they have one and the same URI.
The Resource Description Framework (RDF) is a standard model for data publishing and interchange on the Web developed by the W3C. RDF is the standard used in a semantic graph database, also referred to as an RDF triplestore.
The semantic graph database is technology developed to store interlinked data and make sense of that interconnected data by semantically enriching the datasets. Unlike the relational database, the triplestore maps the various relationships between entities in graph databases. SPARQL, on the other hand, is the W3C-standardized query language for the RDF triplestore.
Still, not all data is freely available and open for anyone to use and share. Open Data is data that can be freely used and distributed by anyone, subject only to, at most, the requirement to attribute and share-alike.
Open Data does not equal Linked Data. Open Data can be made available to everyone without links to other data. At the same time, data can be linked without being freely available for reuse and distribution.
Therefore, the efforts of the W3C community and all advocates of data openness are channeled to enrich Linked Open Data cloud (LOD) .
Linked Open Data is a powerful blend of Linked Data and Open Data: it is both linked and uses open data sources. A graph db for instance is able to handle huge raw datasets from various sources and link them to Open Data, which provides richer queries and findings in data management and analysis. One notable example for a linked open data source is DBpedia, a crowd-sourced community effort to extract structured information from Wikipedia and make this information available on the Web.
Linked Data breaks down the information silos that exist between various formats and brings down the fences between various sources. Linked Data makes data integration and browsing through complex data easier, due to the standards it adheres to. Those guidelines also allow for easy updates and extensions of the data models.
Representing data in a linked way under a set of global principles also increases data quality. In addition, the semantic graph database for representing Linked Data creates semantic links between varied disparate sources and formats and infers new knowledge out of existing facts.
Furthermore, linking open datasets enhances creativity and innovation as all developers, citizens and businesses can use all those datasets to put things into context and create knowledge and apps. For example, Linked Open Data encourages the creation of applications to discover the best neighborhood to live in, based on data on schools, transportation, office buildings and clubs/parks in the area.
Due to the common standards and the open data policy for transparency, Linked Open Data is useful to organizations and society alike.